Ministry of Health and Wellness
MAPPING & SIZE ESTIMATION OF SELECT KEY POPULATIONS IN BOTSWANA
2017
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Table of Contents List of Figure ...... v List of Tables ...... vi List of Maps ...... vii Foreword ...... viii Acknowledgments ...... ix The Writing Committee ...... x List of Acronyms ...... xi Executive Summary ...... xii 1.1. Mapping and Size Estimation Background ...... 1 1.2. Comparative Studies ...... 2 1.2.1. Ethiopia - FSW ...... 2 1.2.2. Zimbabwe and Mozambique - FSW ...... 3 1.2.3. Georgia - FSW ...... 3 1.2.4. Georgia – MSM ...... 4 1.3. Rationale for Conducting Mapping and Size Estimation ...... 5 2. Goal and Specific Objectives of the Mapping and Size Estimation Exercise ...... 7 2.1. The specific objectives of this study are: ...... 7 3. Study Limitations ...... 8 4. Research Methodology ...... 10 4.1. Planning and Consensus-Building ...... 10 4.2. Training of Staff and Field Workers in Protocol and Study Procedures ...... 10 4.3. Selection of Study Sites ...... 10 4.3.1. South-East District ...... 11 4.3.2. North-east ...... 11 4.3.3. Central District and Boteti ...... 11 4.3.4. Ngamiland & Okavango ...... 11 4.3.5. Chobe District ...... 11 4.3.6. Kgalagadi North ...... 11 4.4. Target Population ...... 12 4.4.1. Female Sex Workers (FSWs) ...... 12 4.4.2. Men who Have Sex with Men (MSM) ...... 12 4.4.3. People who Inject Drugs (PWIDs) ...... 13 4.4.4. Trans-genders (TGs) ...... 13 4.4.5. Nationality and Residency ...... 13 4.5. Community Sensitisation & Formative Assessment ...... 13
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4.6. Formative Assessment ...... 14 4.6.1. Scope of Formative Assessment ...... 14 4.6.2. Approach ...... 15 4.7. Data Triangulation ...... 15 4.7.1. Statistics Botswana ...... 15 5. Survey Findings ...... 16 5.1. Geographic Mapping...... 16 5.1.1. Mapping Summaries ...... 16 5.1.2. Formative Assessments ...... 17 5.1.2.1. Gaborone | Kweneng West ...... 17 5.1.2.2. Boteti | Ngami | Okavango ...... 18 5.1.2.3. Palapye | Serowe ...... 19 5.1.2.4. Francistown – Tutume ...... 20 5.1.2.5. Kgalagadi North - (Kang & Hukuntsi) ...... 21 5.1.2.6. Selebi Phikwe | Chobe ...... 22 5.1.3. Mapping Conclusions ...... 23 5.2. Size Estimation ...... 23 5.2.1. Geographic Scope ...... 23 5.2.2. Key Population Scope ...... 24 5.2.3. Female Sex Worker Size Estimates ...... 24 5.2.3.1. Distribution of Hotspots by Health District ...... 26 5.2.3.2. Hotspot by Town & Village Location ...... 27 5.2.3.3. Hotspot Type by Health District ...... 28 5.2.3.4. FSWs Usually Observed (Least Reported) ...... 29 5.2.3.5. FSWs Usually Observed (Most Reported) ...... 31 5.2.3.6. Lowest and Highest Comparative Observations ...... 34 5.2.3.7. FSWs Directly Observed ...... 34 5.2.3.8. Directly Observed Yield (Peak Days) ...... 41 5.2.3.9. Average Yield per Hotspot ...... 42 5.2.4. Sex Worker Diaries ...... 54 5.2.4.1. District Distribution ...... 54 5.2.4.2. Age Range ...... 54 5.2.4.3. The Nationalities ...... 55 5.2.4.4. Clientele Serviced ...... 56 5.2.4.5. Service Pricing ...... 56 5.2.4.6. Factors that Influence Pricing ...... 59
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5.2.4.7. Sexual Activities ...... 59 5.2.5. MSM Estimates ...... 60 5.2.5.1. MSM Mini Survey Findings ...... 60 5.2.5.1.1. MSM Recent Sexual Activity ...... 62 5.2.5.1.2. MSM Access to Health Services ...... 63 5.2.5.1.3. Service Provider Data ...... 67 5.2.5.1.4. Service Multiplier Calculation ...... 68 5.2.5.1.5. MSM Service Satisfaction ...... 70 5.2.6. Transgender Estimates ...... 72 5.2.6.1. TG Mini Survey Findings ...... 72 5.2.7. PWIDs Estimates ...... 76 5.2.7.1. Awareness of PWIDs ...... 76 6. Discussion ...... 78 6.1. FSW Estimates...... 78 6.2. MSM Estimates ...... 82 6.3. TG’s Estimates ...... 83 6.4. PWIDs Estimates ...... 83 6.4.1. BOSASNET ...... 83 7. Conclusion and Recommendations ...... 85 7.1. Geographical Mapping ...... 85 7.2. Separating Mapping & Size Estimation ...... 85 7.3. Peer Outreach Worker Training ...... 85 7.4. Qualitative Data ...... 85 7.5. Size estimation ...... 86 7.6. Building Local MSE Capacity ...... 87 8. References ...... 88 9. Annexes ...... 91 9.1. Local Comparative Hotspot Data ...... 91 9.2. Tools ...... 92 9.3. Additional Data Sources ...... 98 9.3.1. Names of all hotspots visited by District ...... 98
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List of Figure
Figure 1: Number of Hotspots Visited by Day of the Week ...... 25 Figure 2: FSW Yield versus time of Enumeration ...... 26 Figure 3: Number of Hotspots per District ...... 27 Figure 4: Hotspot by Location (Village or Town) ...... 28 Figure 5: Hotspot Type by District ...... 29 Figure 6: Least Number of Female Sex Workers Estimated as Usually Seen by District Informants ...... 30 Figure 7: Most Number of Female Sex Workers Usually Seen by District ...... 32 Figure 8: Comparison of Least and Most Female Sex Workers Usually Seen by District...... 34 Figure 9: Distribution of Actual Time of Day of Directly Observed Census Numeration ...... 35 Figure 10: Hotspot Venue Data Collection Visits by Day of the Week ...... 41 Figure 11: FSW Yield per Hour ...... 42 Figure 12: Average FSW Hotspot Yield by District ...... 43 Figure 13: Estimated Age Range of Female Sex Workers ...... 55 Figure 14: Minimum Average Price for Commercial Sex Services ...... 57 Figure 15: Maximum Price Charged for Commercial Sex Services ...... 57 Figure 16: Factors that Influence the Price Charged for Commercial Sex ...... 59 Figure 17: Age of MSM who Accessed Programme Services ...... 64 Figure 18: Locations where MSM had Obtained Health Services in the last 6 Months...... 65 Figure 19: Frequency Distribution of Services Provider ...... 66 Figure 20: Service Provider where MSMs Receive Services by District ...... 67 Figure 21: Array of Services Received by MSM ...... 71 Figure 22: Service Providers offering MSM HIV Testing and Counselling ...... 72 Figure 23: Age Distribution of Transgender Respondents ...... 73 Figure 24: Type of Services Received by Transgender Respondents ...... 74 Figure 25: Age Distribution of Those who Know PWIDs ...... 76 Figure 26: Statistics Botswana Commercial Retail Outlets ...... 78 Figure 27: Licensed Commercial Outlets versus Directly Mapped Venues ...... 80
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List of Tables
Table 1: Female Sex Worker Methods & Estimates in Zimbabwe and Mozambique ...... 3 Table 2: Greater Gaborone Formative Assessment Conducted ...... 18 Table 3: Boteti, Ngamiland Formative Assessments Conducted ...... 19 Table 4: Serowe, Palapye Formative Assessments Conducted ...... 19 Table 5: Greater Francistown Formative Assessments ...... 21 Table 6: Kgalagadi North ...... 22 Table 7: Selebi Phikwe Formative Assessments ...... 22 Table 8: Number of Hotspots by Circuit ...... 23 Table 9: Number of Hotspots by District ...... 24 Table 10: Key Informant Perception of KPs who Frequent the Venue ...... 24 Table 11: Least Number of Female Sex Workers Usually Seen ...... 29 Table 12: Distribution of Least Number of Female Sex Workers Usually Seen by District ...... 31 Table 13: Most Number of Female Sex Workers Usually Seen ...... 31 Table 14: Distribution of Most Female Sex Workers Usually Seen by District ...... 33 Table 15: Number of Female Sex Workers Directly Observed by District ...... 35 Table 16: Selected Data of Most Frequented Hotspots (Top Twenty) ...... 44 Table 17: Number of Sex Workers Interviewed by District ...... 54 Table 18: Female Sex Worker's Perception of Nationality of other Female Sex Workers ...... 55 Table 19: Estimating Number of Clients on a 'Good Business Day' ...... 56 Table 20: Estimated Number of Clients on a 'Bad Business Day' ...... 56 Table 21: Minimum Service Pricing for Female Sex Work Services ...... 58 Table 22: Maximum Service Pricing for Female Sex Work Services ...... 58 Table 23: Specific Sexual Activities Performed with Clients ...... 60 Table 24: Number of Men who have Sex with Men Directly Interviewed ...... 61 Table 25: Nationality of MSM Interviewed ...... 61 Table 26: Age Distribution of MSM ...... 62 Table 27: Percentage of MSM who had Sex in Last Six Months...... 62 Table 28: MSM having Oral or Anal Sex by Age ...... 63 Table 29: Percent of MSM who Accessed Health Services ...... 64 Table 30: Providers from Whom MSM Received Services ...... 65 Table 31: Service Providers Named by MSM as a Source of Service for their Needs ...... 68 Table 32: Total Estimate of MSM across the surveyed districts ...... 69 Table 33: MSM Reason for Level of Satisfaction with Services Received ...... 70 Table 34: Name of the Type of Service Received ...... 70 Table 35: Transgender Sex in Past Six Months ...... 73 Table 36: Transgender by District ...... 73 Table 37: Transgender Service Received in Last 6 Months ...... 74 Table 38: Transgender Sex in Last Six Months ...... 75 Table 39: Transgender Service Providers ...... 75 Table 40: Location of TG Service Providers ...... 75 Table 41: Knowledge of PWIDs ...... 76 Table 42: Knowledge of PWIDs by District ...... 77 Table 43: Economic Activity by Outlet Type ...... 79 Table 44: Network Scale up Factor Calculation ...... 81 Table 45: Ratio of Female Sex Worker to Total Female Population ...... 82
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List of Maps
Map 1: Distribution of Key Populations across Greater Gaborone ...... 37 Map 2: Distribution of KPs across Central Gaborone ...... 38 Map 3: Distribution of Key Population across Mogoditshane ...... 39 Map 4: Distribution of Key Populations across Tlokweng ...... 40 Map 5: Key Population Presence in Chobe District ...... 44 Map 6: Presence of Key Population Groups across Greater Francistown ...... 46 Map 7: Presence of Key Population Groups in Central Francistown ...... 47 Map 8: Female Sex Worker Intensity in Okavango District ...... 48 Map 9: Female Sex Worker Intensity in Ngamiland ...... 49 Map 10: Female Sex Worker Presence in Boteti Sub-district ...... 50 Map 11: Female Sex Worker Key Population intensity in the Central District ...... 51 Map 12: Female Sex Worker Intensity in Selebi-Phikwe ...... 52 Map 13: Tutume Female Sex Worker Intensity ...... 53
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Foreword
As the world commits to the ambitious goal of ending HIV/AIDS as a major public health threat by 2030, evidence based planning, implementation and monitoring of the response to HIV/AIDS becomes more than ever dependent on our knowledge of the situation on the ground.
The Second National Strategic Framework (NFS II) highlights four priority areas for responding to HIV/AIDS in 2010-2016: 1. Preventing New Infections; 2) Systems Strengthening; 3) Managing Strategic Information; and 4) Scaling up Treatment, Care and Support. To fulfil the first priority, the government noticed that there is need to increase access to HIV prevention services for the most-at-risk populations’ also known as key populations and as a result conducted the first BBSS I in 2012. The result of the BBSS I indicated that there is a need to have a comprehensive exercise to map the KPs and estimate their sizes in more than three districts as previously covered by BBSS I. The Mapping and Size Estimation of Select Key Populations in Botswana Study will help the country in evidence based planning, prioritizing the geographical areas for resource allocation, feed into NSF III and assist in monitoring and evaluating the response by tracking the coverage of KPs. Identifying the key population groups, their locations and their size helps in understanding and prioritizing the current needs for HIV prevention, diagnosis, treatment and care services while helping to project future need for those services.
In order to close the data gaps identified during BBSS I, MOHW in partnership with ACHAP through Global Fund conducted a study (MSE) for Mapping and Size Estimation of KPs namely FSW, TGs, PWID, and MSM in 12 districts namely Greater Gaborone, Chobe, Greater Francistown, Selebi Phikwe, Ngami, Tutume, Serowe, Kgalagadi North, Palapye, Kweneng West, Okavango and Boteti.
The results of MSE came at a time when the country prepares its next NSFIII 2017-21 and when a review of the targeted interventions under the HIV/STI program has been completed. Both results will assist the government as it takes the leadership role in implementation of the prevention strategies among KPs with support from partners.
This technical report is recommended for use in relevant strategies.
______
Ms. Ruth Maphorisa
Permanent Secretary
Ministry of Health and Wellness
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Acknowledgments The Ministry of Health and Wellness (MoHW) would like to extend sincere gratitude to all who contributed to the successful completion of the Mapping and Size Estimation of Select Key Populations in Botswana Survey. The study was carried out by the STI Control Programme in the Department of Health Service Management of the Ministry of Health and Wellness (MoHW) in collaboration with ACHAP.
The members of the above mentioned organizations were instrumental in making the survey a success. Special thanks goes to the writing and validation team members led by Ivor F. Williams in close collaboration with Dorcus Kanyenvu, Boga Fidzani, Mike Merrigan, Lesego Busang, Moemedi Keakantse, Bene Ntwayagae, Botho Matshidiso and K. Kusi for their hard work in the final preparation of the report.
The Technical Working group comprised a range of stakeholders responsible for oversight of the study under the coordination of the Ministry. Members of the TWG included the National Health Laboratory (NHL), the Botswana Police Service, World Health Organization (WHO), the Joint United Nations Programme on HIV/AIDS (UNAIDS), the U.S. Agency for International Development (USAID) and HIV-AIDS and non- governmental organisations that work directly with Key Populations.
The study would not have been possible without the support of the District Health Management Teams (DHMT) of Greater Gaborone, Greater Francistown, Selebi-Phikwe, Chobe, Ngamiland, Boteti, Serowe, Okavango, Kweneng West, Tutume, Palapye, Serowe and Kgalagadi North in facilitating introductory meetings at the district level. Similarly, councils, clinics, hospitals, Village Development Committees (VDCs), tribal leadership, law enforcement and the prisons in the districts are also appreciated for their significant contributions to the survey. Kweneng East DHMT is also acknowledged for the support provided during the pilot phase which was done in Molepolole.
The role of civil society in linking the technical team to the core study population cannot be underplayed. Special thanks goes to LEGABIBO (Lesbians, Gays and Bisexuals of Botswana), Nkaikela Youth Group, Sisonke, Pilot Mathambo Centre for Men’s Health, Rainbow Identity Association, Botswana Family Welfare Association (BOFWA), Silence Kills, Men for Health and Gender Justice, Tebelopele Voluntary Counselling & Testing Centre (TVCT) and Botswana Network on Ethics, Law and HIV/AIDS (BONELA) for these linkages, direct involvement in data collection and for availing their personnel, facilities and expertise to support the study. The study recognizes the specific contribution made by the Botswana Substance Abuse Support Network (BOSASNet) for their independent inputs around the use and abuse of drugs in Botswana.
Special thanks goes to all who directly or indirectly made contributions to the success of the study.
Thank you all!
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Dr. Morrison Sinvula
Deputy Permanent Secretary/Health Services Management
Ministry of Health and Wellness
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The Writing Committee
Ivor Williams ACHAP (Consultancy Unit Manager) Lesego Busang ACHAP (Director Monitoring & Evaluation) Dr. Boga Fidzani ACHAP (Monitoring & Evaluation Specialist) Blessed Monyatsi ACHAP (Head of Projects – Global Fund) Dorcus M Kanyenvu MoHW (STI Control Programme) Bene C Ntwayagae MoHW (STI Control Programme) Moemedi Keakantse ACHAP (Business Development Officer) Dr. Pamela Smith-Lawrence University of Botswana (MMed Public Health Resident)
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List of Acronyms ACHAP African Comprehensive HIV/AIDS Partnerships
AIDS Acquired Immune Deficiency Syndrome
ANC Antenatal Care
BBSS Biological and Behavioral Surveillance Survey
BAIS Botswana AIDS Impact Survey
FGD Focus Group Discussion
FSW Female Sex Worker
DHPC Department of HIV and AIDS Prevention and Care
HCT HIV Counseling and Testing
HIV Human Immunodeficiency Virus
MARPS Most at risk Populations
MOH Ministry of Health
MSM Men who have Sex with Men
NGO Non-governmental organization
NSF National Strategic Framework
PMTCT Prevention of Mother to Child Transmission
PWID People Who Inject Drugs
TWG Technical Working Group
UNAIDS Joint United Nations Programme on HIV and AIDS
USAID United States Agency for International Development
WHO World Health Organization
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Executive Summary This survey maps the geographic locations where key populations congregate and provides an estimate of their number in the selected locations. The survey was conducted in twelve health districts across Botswana, ten which correspond to districts where the Global Fund has on-going activities and an additional two selected from those mapped in the 2012 Biological, Behavioral and Surveillance Survey (BBSS). The 2012 Biological, Behavioral and Surveillance Survey covered three districts. While the findings of this report is mainly based on primary data collection, it has considered a broad range of literature from several similar studies; from Ethiopia, Georgia, Mozambique and Zimbabwe to name but a few. In addition, the Botswana 2012 BBSS study is extensively referred to in order to understand key population dynamics in Botswana over the last five years.
Female Sex Workers The key populations estimated in this study are Female Sex Workers (FSWs), Men who have Sex with Men (MSM), Transgender people (TGs) and People Who Inject Drugs (PWID) for non-health reasons. The population estimate for female sex workers was determined to be 6718 across the 12 study districts as compared to 4000 in three districts in 2012.
Greater Gaborone and Greater Francistown had the highest absolute number of female sex workers in this survey, estimated as 1641 and 687 respectively. Bars were found to be the hotspot type with the most number of female sex workers. The data found a disproportionately higher number of hotspots in Gaborone and Francistown compared to the remaining locations. This implies wide or thinner spread of FSWs across the two city venues. Chobe and Ngami on the other hand had fewer sex workers (directly observed) and also identified significantly fewer hotspots. This resulted in Chobe and Ngamiland having a higher average yield, 26 and 23 FSWs per hotspot respectively, compared to an average yield of 12 and 11 FSWs per hotspot in Gaborone and Francistown.
The range of hotspot types across the survey included bars, street side venues including truck stops, unlicensed shebeens and leaning institutions. A noticeable finding in this survey as compared to the Botswana 2012 is the identification of residential hotspots that operated like brothels, no brothels were identified in 2012. These were specifically found in the Gaborone and Francistown as the country’s two cities but also in Selebi-Phikwe, a mining town with a history of high HIV prevalence.
Men who have Sex with Men This survey estimated the total number of Men who have Sex with Men to be 2625 using the Service Multiplier Method. A total of 339 MSM were directly interviewed while data from service provider registers came to 1884. The highest number of MSM were found in Francistown, over forty percent, followed by Gaborone (24.5%), and ten percent in Selebi Phikwe.
The self-reported age distribution of MSM shows that the bulk of the respondents fall in the age range of 21 to 29 years (70.4%). This distribution resonated with informant sentiments that older men in this key population remain hidden as they are often married and very atypical members of society.
The MSM interviewed were very open and transparent. Over 90% of the men interviewed revealed that they had either anal, oral or both forms of sexual intercourse in the last six months. The youngest age recorded for this sexual activity was 17 years while the oldest was 62 years.
BOFWA, LEGABIBO, Men for Health, Tebelopele and Silence Kills were identified as the leading service providers to MSM. Nearly a quarter (22.59%) of the respondents did not access services over the past six months, from a programme targeting MSM. Some MSM disclosed receiving health services from government facilities and expressed satisfaction with the services received. The government facilities on the other hand did not have records to quantify the number of MSM serviced saying that all clients are treated equally and the record keeping system does not provide to recording KPs as a separate group.
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MSM expressed that the services most sought after were those related to HIV Testing and or counselling; this was needed far more than any other service. Condoms, lubricants and other clinical treatments, though named as services received was received by a very low number of respondents.
Transgender People TGs were identified through snowballing. This involved working with seed respondents who directed study teams to other TGs within their network. This process was continued until the network was exhausted. A total of 47 TGs were directly interviewed with the majority of them found in Gaborone (80.9%). TGs cited stigma and discrimination as the main challenges they encounter as they struggle to find acceptance even among their families.
Under sixty percent of the TGs interviewed said they are able to access the health services that they need with counselling being the service most accessed. The level of satisfaction recorded 93.1% saying that they were satisfied with the services they received. BOFWA, Health Empowerment Rights, LEGABIBO, Rainbow Identity and Tebelopele are the service providers named by TGs from where they obtained services. One respondent named a private practitioner as their provider while no government facility was named as a targeted service provider. People Who Inject Drugs No PWIDs were found in this study. Vast attempts were made to include this group in the survey through interviewing civil society groups that work directly with substance abuse and asking MSM and other key informants if and how their networks may cross with that of PWIDs. Almost 16% of all the MSM interviewed said they know of at least one person who injects drugs. This infers that there are at least 54 individuals believed to be using drugs through injectable methods. The respondents were however not able to definitively direct the research team to any of the PWIDs to have a direct interview with them, hence the reported figure of no PWIDs.
Those who say they know PWIDs are largely in the 20 to 30 year age group. The majority of those who say they know people who inject drugs are in Greater Francistown (79.6%) followed by Greater Gaborone (18.5%).
The study explores and offers some reasons as to why PWIDs have been nearly impossible to locate both in this study and in 2012. This results show that PWIDs in Botswana are a relatively small number who are well hidden within their networks.
Conclusion The Botswana 2012 BBSS study is the only local yardstick available to directly compare KP size estimation over the last five years. The 2012 study however used different methodologies in its FSW and MSM size estimation. That study did not include TGs and PWIDs. Global literature shows that variation in methods used can greatly affect the final estimate. The previous study was only conducted in three districts while the present is in 12. Taking all these factors into consideration it appears that MSM and TGs have grown in number more rapidly than FSWs. Additionally, based on the perceptions of key informants it would appear that the number of PWIDs may also be growing but as a very carefully hidden network.
The reasons for the leveling off of the FSW population and the growth in the other three groups are beyond the scope of this study. The purpose of this study was to provide size estimates for key populations, which are provided herein. The numbers however provide sufficient level of curiosity to warrant in-depth investigation on the social and behavioral dimensions surrounding key populations in
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Botswana. The numbers also offer a sample frame for interrogating the disease burden in the three groups (FSW, TGs and MSM) across the districts in which they have been found.
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1. Introduction The population of Botswana was estimated at 2,024,904 in 2011 (Statistics Botswana, 2011). Its HIV Prevalence of 18.5% and Incidence of 1.35%, both measured through the Botswana AIDS Impact Survey of 2013 (BAIS IV) placing it among countries most affected by HIV in the world. Females have higher estimated HIV prevalence of 20.8% compared to men with an estimated prevalence of 15.6% (BAIS, 2013). HIV Prevalence is also higher in urban areas (19.2%) than in rural areas (17.2%).
Botswana has garnered immense recognition in her decade long fights against the epidemic; from the dark period in the 90s and early 2000s where deaths from AIDS afflicted families’ country wide to the present where the epidemic is seemingly under control. This remarkable shift has been gained through heavy financial investments by the government and international donors. Though much progress has been made, much work still remains to truly stem the scourge of the disease.
The AIDS epidemic in Botswana is a generalised epidemic with transmission occurring primarily in the general population. As a result, significant prevention resources have been devoted to interventions directed at the general population. More specifically, Botswana has achieved notable success in scaling up care and treatment as well as Prevention of Mother to Child Transmission (PMTCT) interventions to over 90%.
In keeping with tracking generalised epidemics, Botswana’s second generation HIV/AIDS surveillance systems have in the past consisted of sentinel surveillance among pregnant women attending ANC clinics and household surveys (such as BAIS) tracked HIV prevalence, knowledge and attitudes, and risk behaviors amongst the general population. As the HIV epidemic matures, such surveys must be complemented by targeted behavioral surveys among sub populations since it is difficult to adequately cover them in population-based research. Such surveys are better suited to capture trends or changes in both high-risk and protective behaviors among these generally hard to reach populations.
Mapping and Size Estimation of key populations is therefore an important starting point in conducting targeted surveys among key populations as it will provide not only the estimates for the key populations, but also the sampling frame for other surveys and targeted key population interventions.
1.1. Mapping and Size Estimation Background Botswana is known on the African continent for its long-established HIV surveillance systems that track infection in pregnant women. These studies have been vital from monitoring trends in sexual behavior and devising programmes to arrest the spread of HIV in the general population. The situation for ‘Key’ and or ‘Hidden Populations’ is markedly different. Studies from around the world report that there is, “No standardised methodologies currently available to guide this process (of estimating the size of these key populations), in Asia, Latin America and Eastern Europe, where HIV is more heavily concentrated in sub-populations with defined risk behaviours, more and more governments are now investing in surveillance systems that track the distribution of the virus and the behaviours that spread it in the hardest-hit populations”. Notwithstanding these global attempts, even the best existing surveillance systems have a key weakness. While these systems are able to measure the level of risk behaviour, HIV and STI infection in a given sub-population, they cannot give any indication of the absolute size of the
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 1 sub-populations. As a result of this limitation, many countries, including Botswana, have begun to attempt to estimate the size of populations at high risk through many different approaches1.
The first comprehensive survey among key populations in Botswana was the Mapping, Size Estimation & Behavioral and Biological Surveillance Survey (BBSS) of HIV/STI among Select High-Risk Sub-Populations, in Botswana, (2012) conducted by the Ministry of Health and FHI. It collected biological and behavioral data from Female Sex Workers (FSWs) and Men who have Sex with Men (MSMs). Attempts to include People Who Inject Drugs (PWIDs) were not successful due to prohibitively low response rates. The survey was conducted in Gaborone, Francistown and Kasane. It estimated that there were 4 000 FSWs and 781 MSMs in the three districts as well as prevalence rates for these populations. This study is however restricted to Mapping and Size Estimation of Female Sex Workers, Men who have Sex with Men, Transgendered people and People Who Inject Drugs. It also provides the sampling frame for the 2017 Microbial and Biological, Behavioural Surveillance Survey (BBSS) planned for later in the year.
The current study aims to build on the 2012 study by:
Increasing the number of key populations of interest to include Transgendered People (TGs) and People Who Inject Drugs (PWID) and; Increasing the number of districts from three (3) in 2012 to twelve (12) in 2017.
1.2. Comparative Studies In order to gain a deeper appreciation of the processes, challenges and findings associated with mapping hidden populations evidence was gathered from studies elsewhere around the world.
1.2.1. Ethiopia - FSW Family Health International (FHI) undertook a Mapping and Census of Female Sex Workers in Addis Ababa in 2002 in collaboration with the City Administration Health Bureau2. The history and longevity of Ethiopia as well as the population of Addis Ababa (2,623,972) in the city alone, which is equivalent to that of Botswana, allows for some analogies to be drawn. In the Ethiopia study for example, “After considering several population size estimation methods, it was decided that a census of sex workers would provide the best information for program planning and evaluation”, which is the same methodology used in the current Botswana survey.
Similarly, one of the key objectives of the Ethiopia Study was to identify establishments and specific locations where sex workers are found. Data in Ethiopia, as in Botswana was collected from drinking and/or eating establishments (including hotels, bars, restaurants, night clubs, pubs, tella, araki and tej bets, and others). These establishments date back to the 1950s and 1960s. Each of these establishments, or ‘hotspots’ was approached based on guidance from ‘Peer Outreach Workers’ and mapped whether or not sex workers were actually found to be present. Commercial sex work in Ethiopia is traced back to the ‘olden times’ with some sources associating the beginnings of commercial sex with the movement of kings, nobles and warlords, the establishment of cities and the development of trading (Andargachew 1988).
1 Pisani, E. (2002), Estimating the Size of Populations at Risk, Issues and Methods, Updated July 2003, UNAIDS, Impact, FHI; ISBN 974-91495-0-5 2 Mapping and Census of Female Sex Workers in Addis Ababa, Ethiopia A study undertaken by Family Health International (FHI) – Ethiopia in collaboration with the Addis Ababa City Administration Health Bureau (AACAHB); August 2002.
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Regardless of the long history of commercial sex, commercial sex work is not a legally recognized ‘profession’ in Ethiopia, as is the case too in Botswana, which hence pushes the populations into ‘hiding’. Regardless of the illegality, most of the establishments where the sex workers are based (hotels, bars/restaurants, night clubs etc.) operate legally with working licenses.
1.2.2. Zimbabwe and Mozambique - FSW The most recent size estimate studies for sex work populations in Zimbabwe date back to the early and mid-1990s. In 1992, a capture-recapture study was conducted in Bulawayo which estimated the population of women socialising in a random selection of bars as 3894 (95% CI: 4184-3644). The total bar-based sex worker population in Bulawayo was estimated at ~9500 bar-based sex workers; including women who did not solicit in bars, the total sex worker population in Bulawayo was estimated at almost 12,0003. A similar capture recapture study in Mutare, estimated that between 1600 and 2000 women were selling sex over the two weekends of the study4.
Data from Tete province in Mozambique which lies on a major trucking route from Zimbabwe and where a third of the population attending the clinic were Zimbabwean shows that sex worker to the general female population ranges from as low as 2.4% sex workers per female population to as high as 18% depending on the method of enumeration used.
Table 1: Female Sex Worker Methods & Estimates in Zimbabwe and Mozambique
Location Year Total Pop'n Female Pop'n De Facto De jure SW/female Method of size Size Pop'n pop'n pop'n (15-49) Enumeration %
Chirundu 1999 2,700 – 4,000 1,092 – 1,618 100 300 6.2 to 18.5 Mapping Beitbridge5 1999 20,000 10,528 500 700 4.7 to 6.6 Mapping Mutare 1993 131,367 66,000 1600 to 2.4 to 3.0 Capture-Recapture 2000
Bulawayo 1994 621,742 173,841 9500 to 5.4 to 6.9 Mapping & Capture- 12000 Recapture
Mashonaland6 2003 2,007 363 18 Ethnographic Mapping
Tete & 2008 48,500 4,415 9.1 Mapping & Moatize Enumeration
1.2.3. Georgia - FSW This study was undertaken in Tbilisi and Batumi within a GFATM funded project. Multiple methods were used for FSW population size estimation in Tbilisi and Batumi; including the “network scale-up method”,
3 Ngugi EN, Wilson D, Sebstad J, Plummer FA, Moses S. Focused peer-mediated educational programs among female sex workers to reduce sexually transmitted disease and human immunodeficiency virus transmission in Kenya and Zimbabwe. Journal of Infectious Diseases. 1996;174:S240-S7. 4 Watts C, Zwi A, Wilson D, Mashababe S, Foster G. Capture-Recapture as a Tool for Program- Evaluation. Br Med J. 1994;308(6932):858-. 5 Based on entire female population 6 Males only
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“census”, “capture-recapture”, “service multiplier method”. The last two methods were conducted in conjunction with the BBS. This is a valuable study to look at because of its vast differences to Botswana, allowing for contrast and a wide perspective of how estimating key populations can differ across the globe and yet still show similar outcomes. Georgia is a country with extremely low HIV prevalence but with a high potential for a widespread epidemic. The origins of HIV transmission in years gone by was linked to injecting drug use but more recently heterosexual transmission has been on the rise, almost half of all new infections in 2012 and 2013 being heterosexual7.
Prevalence of FSW according to the NSU (Network Scale-up Method) is 1.03% in Tbilisi and 2.42% in Batumi. Comparisons of Georgia estimates (from the NSU method) with the regional estimates indicate Georgia FSW prevalence is within the range of regional recommendations of UNAIDS. NSU figures represent estimates for all types of FSWs, while other methods count mainly street and facility based FSW and those who benefit from free HIV testing offered by the preventive programs.
This study also supports the essence of estimating key populations against the general population, in the case of Female Sex Work it highlights the value of looking at total population data for female in reproductive age groups and presents FSW estimates as a proportion of the total. The study also draws comparisons from an array of Eastern European cities for triangulation purposes that include Kutaisi, Telavi, Poti, Zugdidi, Rustavi and Gori.
1.2.4. Georgia – MSM Unlike in Botswana, homosexuality has been decriminalized in Georgia. However, this has not resulted in MSM coming out as issues of stigma and discrimination still persist, making it equally difficult to estimate the MSM population. In recognition of the need to accurately estimate the population size of MSM as part of the response to the HIV epidemic a study was conducted in Tbilisi, Georgia8. As there is no gold standard for estimating the population size of MSM, the study utilized several size estimation methods including network scale-up, mobile/web apps multiplier, service and unique object multiplier and network based capture—recapture. A respondent driven sample of 210 MSM was done, a figure slightly below the current study’s directly observed MSM mini-interviews.
The service multiplier method involved the use of programmatic data from a health centre, which was cross-referenced with data collected from respondents about the utilization of services over the six months prior to the survey. These parameters are exactly identical to the present study and allow us to make comparisons between the two. Using all the methods, a population estimate of 4541 MSM was given. The service multiplier method alone yielded an estimate of 1980 MSM based on the data from one health centre which reported that 333 utilized the services available to them. Since the current study utilized data from a larger number of service providers, the MSM estimate for the current study using the service multiplier method is expected to be more than the 1980 from Tbilisi.
7 Chikovani, I., Shengelia, N., Sulaberidze, L. & Tsereteli, N. (2014), Population Size Estimation of Female Sex Workers in Tbilisi and Batumi; Georgia 2014. 8 Sulaberidze, Lela et al. “Population Size Estimation of Men Who Have Sex with Men in Tbilisi, Georgia; Multiple Methods and Triangulation of Findings.” Ed. Ruan Yuhua. PLoS ONE 11.2 (2016): e0147413. PMC. Web. 27 July 2017.
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1.3. Rationale for Conducting Mapping and Size Estimation The National Strategic Framework (NSF II) 2010-2016 stipulates the need to increase HIV prevention services for most at risk and hard to reach populations as one of its prevention implementation strategies. However, very little is known about sub-populations in Botswana thought to be at high risk of HIV infection such as sex workers, sexual minorities, prisoners, and people who inject drugs (PWIDs).
In sub-Saharan Africa, female sex workers have a 12-fold increase in the odds of being HIV infected compared to all women of reproductive age9. The high risk of HIV infection is due to the high number of sexual partners FSWs have and the frequency of their sexual encounters. The high HIV prevalence of 61.9% among female sex workers in Botswana is consistent with global findings that FSWs are disproportionately affected by HIV. Issues of stigma, poverty, and gender-based violence coupled with the illegality of sex work and discriminatory healthcare services further contributes to the elevated risk of HIV infection among this population. As Botswana aims to build on the gains achieved over the years in combating HIV, it is crucial for prevention efforts to be intensified in this sub-population as part of the national response to HIV/AIDS. This includes making sure that FSWs use protection at all times, are able to negotiate with clients for safer sex, health-seeking behavior is strengthened among FSWs so that they are regularly tested for HIV/AIDS and other STIs, and take treatment upon infection. Engaging FSWs in this response will ultimately bring about safer sex work and reduce HIV infection among this subpopulation so that they live longer and healthier lives.
HIV prevalence among men who have sex with men is significantly higher than HIV prevalence in the general population, even in the context of generalized epidemics10. Research suggests that there is greater risk of HIV transmission among MSM through receptive anal intercourse that is 18 times higher than that of penile-vaginal sexual contact11. Despite the elevated risk of HIV for this key population, 76.3% of MSM in Botswana were unaware of their HIV status and a significant number reported unprotected anal intercourse (Baral et al., 2009). There is therefore need to first have an accurate estimate of the MSM population in Botswana so that prevention efforts are scaled up for this key population as part of the wider national response.
Additionally, evidence suggests that high-risk populations can transmit HIV to their regular partners (married and non-married) and therefore to the general population (Baral et al., 2009; Merrigan et al, 2011). Sex workers and MSM have additional sexual partners amongst the general population. Clients of FSWs also engage in unsafe behaviors with other partners such as wives or girlfriends and thus act as a bridge for the spread of HIV from high risk populations to lower risk individuals in the general population. Given the relatively limited information available about these sub-populations, there is a need for robust data to determine whether certain sub-populations contribute disproportionately to HIV transmission. Therefore, bio-behavioral surveys which generate accurate data on the population size of these sub-populations, their risk behaviors, HIV prevalence and HIV incidence are crucial for Botswana’s
9 Fonner, Virginia A. et al. “Social Cohesion, Social Participation, and HIV Related Risk among Female Sex Workers in Swaziland.” Ed. Cédric Sueur. PLoS ONE 9.1 (2014): e87527. PMC. Web. 27 July 2017. 10 Park, Ju Nyeong et al. “HIV Prevalence and Factors Associated with HIV Infection among Men Who Have Sex with Men in Cameroon.” Journal of the International AIDS Society 16.4Suppl 3 (2013): 18752. PMC. Web. 27 July 2017. 11 Wirtz, Andrea L et al. “HIV among Men Who Have Sex with Men in Malawi: Elucidating HIV Prevalence and Correlates of Infection to Inform HIV Prevention.” Journal of the International AIDS Society 16.4Suppl 3 (2013): 18742. PMC. Web. 27 July 2017.
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2. Goal and Specific Objectives of the Mapping and Size Estimation Exercise The goal of this mapping and size estimation exercise is to establish the geographic location and estimate population size of key populations in Botswana. This information will help the national response to HIV and AIDS to better plan and target programmes and interventions to reduce the spread of HIV and other STIs among these sub-populations as well as the general population.
The survey was limited to twelve districts across Botswana, ten (10) of which are where the Global Fund is currently working while the additional two (2) districts were selected from those that were previously mapped in the 2012 BBSS Survey to allow for any changes to be observed.
2.1. The specific objectives of this study are: i) To establish geographic hot spots where key populations are found in the 12 districts ii) To estimate the size of four populations namely FSW, PWID, MSM and TG in these 12 districts iii) To strengthen the capacity of local institutions to conduct mapping and size estimation of key populations in Botswana.
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3. Study Limitations The limitations of this study have in many ways been similar to those experienced elsewhere across the globe. The first and often most difficult issue is in defining the population whose size one wishes to estimate. In public health terms, we are really most concerned with people whose behavior puts them at risk for HIV. That may be not all members of a defined population.
The second limitation is that not many service providers of key populations had readily available records on sexual orientation hence it was not always possible to estimate how many MSM are their clients thus this could have affected the use of the Service Multiplier method. Government clinics in particular cater to the general population and even though some respondents cited government facilities as places where they received services the service multiplier method cannot work for the government facilities as there is nothing to cross-reference with from government facilities.
Same-sex relationships are illegal in Botswana, resulting in MSM hiding their sexual orientation in fear of possible sanctioning by authorities. The high level of stigma attached to having sex with other men is a critical barrier as many MSM fear ridicule and judgement from their societies; both for themselves and their families and hence remain ‘in the closet’. As this community needs an ‘insider’ for them to open up, we had to rely heavily on the seed respondent and potentially missed the MSM who were not in the seed respondents’ networks.
Transgendered individuals also face a lot of stigma and discrimination, they are often ostracized by their community and even their families so they stay hidden. As snowballing was the only technique that could be used to find this population the study relied on the number and quality of respondents to point the study team to other TGs. In some instances, the seed respondents were uncomfortable ‘outing’ other TGs which meant that those TGs could not be counted. Some TGs would agree to participate in the survey only to pull out at the last minute. As was the case with MSM this community also needs an ‘insider’ for them to open up, making it difficult for the study team to directly engage with TGs.
PWIDs could not be identified in this study. Substantial efforts were made to locate this population through engaging BOSASNET and asking MSM if they knew of any PWIDs. In the focus group discussions participants were also asked if they knew of any PWIDs. One key informant who was a TG mentioned that they knew someone who could point the team to PWIDs but the lead fizzled out as attempts to follow up proved futile.
It was decided that FSW observations will take place at periods of high economic activity, which is usually at month end when FSWs are most likely to be out soliciting clients. Though this was expected to yield the highest number of female sex workers, not all FSWs go to hotspots; hence the team could have missed some female sex workers. New technologies and applications for partner identification is a phenomenon not seen in most alternative studies. These have created new hook-up methods that make the populations more hidden.
As the team relied on KIIs to point them to hotspots some hotspots unknown to the key informants could have been missed in the mapping exercise. FSWs are highly mobile, moving constantly from place to place in search of clients which could have resulted in double counting. The advent and widespread use of social media enables FSWs to appoint with clients from the comfort of the means and therefore those sex workers would not have been counted.
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Some owners/managers of hotspots were uncomfortable discussing the presence of sex work at their establishments which lowers the estimate. Although considerable efforts were made to use peer outreach workers from the FSW community to help identify and count FSWs chances of wrongly identifying some women as an FSW still exist, especially in busy hotspots with a lot of revelers.
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4. Research Methodology The study methodology utilized a cross-sectional descriptive technique that relied on Key Informants (KIs) and Focused Group Discussions (FGDs) during the formative stage. Different methods were then used to map and estimate the size of the four key populations under study. The Census Size Estimation method was used for the FSW population while the Service Multiplier Method was used for MSM. The method used for TGs and PWID was key informant based, relying on key informants to serve as ‘seeds’ from which a snow-balling technique was used to identify as many members of the key populations to a point of saturation.
4.1. Planning and Consensus-Building This phase began with the review of relevant background documents and the scientific literature and has led to the establishment of mechanisms, processes, and structures for continuous dialogue and exchange of ideas and experiences on the Mapping and Size Estimation among the key implementing partners and other stakeholders. The process included the following activities: i) Review of background and technical materials on the population sizes of Key Populations current programs and interventions directed at these subpopulations in the country, and problems related to accessing these populations ii) Meetings and consultations with local experts and potential partners (including members of existing technical working groups) to review the protocol and ensure compliance with highest research and ethical standards iii) Agreement on processes and timelines to be followed in order to successfully deliver this exercise and avoid conflict with other national surveys
4.2. Training of Staff and Field Workers in Protocol and Study Procedures ACHAP trained all the staff who were a part in this exercise. Interviewers and field supervisors were trained on how to recruit, screen and gain consent of prospective participants; how to conduct FGDs and interviews with key informants using the guides developed specifically for the study. In addition, the field supervisors also received refresher training on how to organize, coordinate and supervise data collection activities in their respective sites, including onsite checks prior to data final submission. This ensured that the manual data entry would experience minimal flaws and reduced need to call backs to district sites. Once in Gaborone further verification and cleaning was undertaken in preparation for analysis.
4.3. Selection of Study Sites The study sites included in the survey widely encompassed every cardinal directionality from the south and south-east; the north - south corridor, areas in the north-east; the Central District including Boteti sub-district; the north-west and Ngamiland Districts as well as parts of the Kgalagadi. The formal administrative districts covered by the survey were selected and named in the study protocol as; Tutume, Francistown, Selebi-Phikwe, Palapye, Serowe, Boteti, Ngamiland, Okavango, Kgalagadi North, Gaborone, Chobe and Kweneng West. A brief description of the district and location settings is presented here.
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4.3.1. South-East District The capital city and surrounding locations which spills into Kweneng-East and includes the areas of Gabane, Mmopane, Phakalane, Tlokweng and Modipane (in Kgatleng) fall into this area. These locations are known as the Greater Gaborone Area and were all included in the survey.
4.3.2. North-east ‘Greater Francistown’ which includes Tutume, Nata, Gweta, Dukwi, Mosetse, Serule and Sebina were also part of the study. Francistown is the country’s second city and lies within a 150 kilometre radius from the Zimbabwe border.
4.3.3. Central District and Boteti The Central District rests in the heart of the country’s north-south corridor along the eastern side of Botswana. This corridor is a major route that links South Africa and Zimbabwe which is the main trade route and is home to the largest population settlements in the country.
4.3.4. Ngamiland & Okavango The tourist centre of Maun is the centre of this district. Maun is the gateway to the Okavango and the Delta in the north. The major population centres included in the Okavango catchment area were Gumare and Shakawe.
4.3.5. Chobe District Kasane and Kazungula are twin locations along the Chobe River where Kazungula is the border crossing into Zambia and Zimbabwe. This is hence a key location where trucks park for extended days waiting to make their entry into the rest of Africa. The district has an international airport and is popular with tourist from around the world.
4.3.6. Kgalagadi North The Kgalagadi on the western side of the country is much less populated, desert and rural. Good road network and communication however make this a preferred transport route through which the Trans- Kalahari connects Botswana to Namibia.
The selected locations offer a good representation of both urban and rural Botswana. These are a fair inclusion of mining towns, tourist locations, major population and business districts as well as small sparsely populated settlements. Given the vast geographical spread of these locations, some being almost two thousand kilometres apart the study sites were grouped into six circuits to facilitate the movement of research teams across the country. The circuits were: CIRCUIT NUMBER LOCATION 1 Gaborone | Kweneng West 2 Boteti | Ngami | Okavango 3 Palapye | Serowe 4 Francistown - Tutume 5 Kgalagadi North - (Kang & Hukuntsi ) 6 Selebi Phikwe | Chobe
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4.4. Target Population The target populations were four sub-populations: female sex workers (FSW), men having sex with men (MSM), trans-genders (TG) and people who inject drugs (PWIDs). These subpopulations were selected by the TWG because they are considered to be at high risk for HIV infection in Botswana.
4.4.1. Female Sex Workers (FSWs) In this study, a female sex worker (FSW) was defined as any female, 16 years old or older, who reports having provided sexual services to someone other than her established partner in return for payment in cash or in kind in the last 3 months. Researchers often distinguish two subtypes of sex workers based on where they get their clients: i) Home or brothel-based FSWs who operate from their homes (includes transactional-sex) or from specific well-known fixed locations; and ii) Street based or mobile FSWs who actively seek sexual clients in bars, hotels, discotheques, popular restaurants and hot spots, parks, malls and streets. They are not tied to a fixed location and usually move from one site to another to look for clients.
The settings in which sex work may occur range from brothels or other dedicated establishments to roadsides, markets, petrol stations, truck stops, parks, hotels, bars, restaurants and private homes, and may be recognizable or hidden. Sex work settings may cater to local communities or primarily involve transient, migrant and mobile populations of both sex workers and clients. Depending on their individual circumstances, sex workers may be further victimized by discriminatory gender-based attitudes, violence, and sexual exploitation, and by membership in other populations that are highly vulnerable to HIV exposure, such as men who have sex with men and injecting drug users12. Policies and programmes to address the links between HIV and sex work must recognize the social and geographic diversity of sex work, as well as the rapid changes that may occur in patterns of sex work, including types of transactional sex13 and in sex work settings14. This survey mirrored these global norms and hence reports on the findings within these definitions.
4.4.2. Men who Have Sex with Men (MSM) In this survey, a MSM is defined as a male age 16 years or older who reports having had any type of sex (oral, manual, or penetrative), paid or unpaid, with another male within the last 6 months, as determined by the individual’s responses to a set of screening questions (see Appendix E: MSM eligibility screening questions) related to MSM sexual behavior. Men reporting having had sex with both men and women were also classified as MSM.
12 Key populations includes women and girls, youth, men who have sex with men, injecting and other drug users, sex workers, people living in poverty, prisoners, migrant labourers, people in conflict and post conflict situations, refugees and internally displaced persons as defined in UNAIDS (2005) Intensifying HIV Prevention. UNAIDS Policy Position Paper. 13 Surtees, R (2004), Traditional and Emergent Sex Work in Urban Indonesia. Intersections: Gender, History and Culture in the Asian Context, Issue 10, August 20. http://www.sshe.murdoch.edu.au/intersections/issue10/surtees.html 14 UNAIDS (2006), Report on the Global AIDS Epidemic; TAMPEP European Network for HIV/STI Prevention and Health Promotion among Migrant Sex Workers (2007) Institutional Strengthening and Support for HIV Prevention Activities, Report produced for UNFPA
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4.4.3. People who Inject Drugs (PWIDs) Using or sharing contaminated injection drug equipment is an extremely efficient way of transmitting or acquiring HIV & STIs. The survey defined PWIDs as any male of female that reports having injected drugs for non-medical reasons at least once in the last 6 months.
4.4.4. Trans-genders (TGs) According to UNAIDS (UNAIDS Terminology guidelines, 2015), Transgender is an umbrella term to describe people whose gender identity and expression does not conform to the norms and expectations traditionally associated with their sex at birth. Transgender people include individuals who have received gender reassignment surgery, individuals who have received gender-related medical interventions other than surgery (e.g. hormone therapy) and individuals who identify as having no gender, multiple genders or alternative genders. Transgender individuals may self-identify as transgender, female, male, transwoman or transman, transsexual, or one of many other transgender identities, and they may express their genders in a variety of masculine, feminine and/or androgynous ways. The survey made every effort to separately study transwomen and transmen.
4.4.5. Nationality and Residency Individuals in Botswana are generally mobile, moving from their home base to the lands and or to cattle posts. Female Sex Workers are no exception to this and are actually a lot more mobile due to the nature of their work. In addition, several of the study sites in this survey are border towns close to South Africa, Zambia and Zimbabwe with others on route to Namibia. These present conveniences for FSWs who track long distance truck drivers as their clients and harp on the relatively higher level of economic status, stronger currents and purchasing power of Batswana relative to all its neighbours. Given the focus of this study on surveillance and reducing the spread of HIV and other STIs, the nationality and residency status of potential participants (i.e. whether the person is a citizen of Botswana or not, or a legal or illegal resident of Botswana) will not be considered as criteria for including or excluding potential participants from the study.
4.5. Community Sensitisation & Formative Assessment Sensitisation visits were undertaken in all of the selected sites. Senior members of the research team accompanied by government Ministry of Health and Wellness Staff visited all of the districts. The point of entry into the districts were the District Health Management Teams as the study was coordinated from a health perspective. Community Sensitisation workshops were conducted in all of the circuits.
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NK = Nkaikela, PM = Pilot Mathambo Centre For Men’s Health, LE = LEGABIBO, BON = BONELA SS = Sisonke
The District Multi-sectoral AIDS Committees and the private sector were essential feeders into the communities as these populations use commercial centres for accessing clients.
The community officers attending stakeholder meetings included Social and Community Development (S&CD) officers; Traditional Leaders (Kgotla); Local Police for security and awareness as well as politicians and local civil society groups as well as other district based interest groups.
4.6. Formative Assessment
4.6.1. Scope of Formative Assessment Prior to launching the mapping and size estimation field activities, formative assessments were conducted in all the selected districts. The goal of the formative assessment was to obtain background information about the study of sub-populations (including the types of locations where they congregate, or can be accessed, their beliefs and perceptions regarding STI & HIV risk, HIV & STI prevention) how to approach different subgroups for recruitment in the study, current programmes and available resources in the communities to support the study, and potential logistical and other challenges and how to overcome them.
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4.6.2. Approach The formative assessment was conducted through the use of qualitative methods of data collection including the review of secondary data; semi-structured interviews with key informants (using interview guides); focus group discussions (FGD) with relevant groups; and iv) confirmation of FSW venues through personal observation and lastly through the Key Informant Interviews (KII).
4.7. Data Triangulation The study methodology determined the need to triangulate data against independent national statistical data to the best extent. Efforts were hence made to obtain data from national entities that are known to routinely collect data from commercial entities or those that are mandated with the responsibility of registering businesses. The specific institutions in Botswana that fall into this category are the national or central statistics office known as Statistics Botswana, the Registrar of Companies (CIPA), individual town councils and the chamber of commerce equivalent knows as Business Botswana.
4.7.1. Statistics Botswana
Best results in obtaining independent information was received from Statistics Botswana on commercial businesses from around the country. Data was shared from a wide range of categories that include registered businesses in the agriculture and forestry sector; mining and quarries; manufacturing; energy and waste management; construction as well as the wholesale and retail business sector including tourism data, of which the latter (wholesale, retail and tourism) contained the closet comparable data to that required for mapping and size estimation of key populations.
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5. Survey Findings The findings are divided into two sections, the first section presenting geographic mapping of female sex workers hotspots. This section also covers information around identification for seed respondents of MSMs TGs and PWID. The second part of the findings is on Size Estimation which presents the actual estimates of the key populations based on this study.
5.1. Geographic Mapping The mapping exercise allowed the survey to establish where the geographic hotspots in all the twelve districts15 are where the key populations are found. This was important in providing an understanding of the types of locations that the target populations prefer to congregate. This information is useful in guiding targeted interventions for these populations. It will also be used as a sampling frame for the biological and behavioral survey that follows this survey. Geographic mapping was not used for MSMs, TGs and PWIDs. Instead these populations were reached through snowballing and intelligence of civil society groups that work in the particular realm of key populations as they are not necessarily found in hotspots in the same way as FSW.
5.1.1. Mapping Summaries The main approach for the mapping exercise in all of the districts and survey circuits was to make an initial introduction to the District Health Management Team (DHMT). This was useful to allow the district health teams to link the sensitization visits made a month earlier to the fact that the actual survey work as it commenced. Most DHMTs made the link, welcomed and where possible assisted the field teams with the mapping exercise. Introductions were also made to the village and district leadership such as the District Commissioners office, as well as to the police and prison services, civil society organisations and the social and community development officers.
15 Global Fund Districts vary from the political and administrative districts
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5.1.2. Formative Assessments Formative Assessments constituting key informant interviews, mini service provider surveys, and focus group discussions were held in each of the mapping locations.
5.1.2.1. Gaborone | Kweneng West Setting up appointments for the formative assessment in this circuit was a challenge, even though the district team was readily available, most key informants who were required for direct interviews were not. Efforts to meet during the mapping exercise with relevant individuals at the district level proved futile due to scheduling conflicts in Kweneng while a KII was successfully held with the Gaborone DHMT. Information emanating from this interview was helpful in pointing us to officers who could provide more detailed information. A key informant at Tlokweng Village Development Committee (VDC) was an additional resource that offered the names of hotspots which included bars, hostels and a truck stop in the greater Gaborone area.
The Botswana Family Welfare Association confirmed that they assist key populations in the Greater Gaborone area with a particular focus on MSM and FSWs. Nkaikela Youth Group was another group that focuses on FSWs while Rainbow Identity is an organization that works with TGs and Intersex individuals and usually have events that are able to bring TGs together. The research team was able to identify MSM seed respondents who revealed that MSM usually congregate at certain entertainment areas in Gaborone. The hidden nature of the populations consistently required that the research team was accompanied by ‘in-siders’ of the populations being approached. These ‘seed’ key informant meetings highlighted that several MSM are not happy to frequent these public entertainment venues and as such remain impossible to reach directly further complicating the size estimation objective of the study.
In a FGD held with TGs and FSWs it transpired that there was a lot of stigma faced by KPs. This included derogatory words from the public and judgement when attempting to access services at health facilities. FSWs in particular face stern criticism due to frequently going to clinics with the same STIs and this results in them shying away from visiting health facilities for services for fear of reprisal. Data from service providers, both public and private across the surveyed districts consistently expressed that “we”, service providers treat all patients in the same manner. Service providers stand firm in the comment that unless a patient outwardly presents as a specific KP member then they have no way of telling that someone has alternative sexual preferences. Some service providers explained with evidence that their patient registered do not have room to enter KP specific data while other express that even if they are told, that would not change the treatment regime. FSWs particularly were of the view that legislation that protects their rights should be enacted.
There was a lot of information on which places to find FSWs in Gaborone from the KIIs and FGD which the team was able to verify with the help of Peer Outreach Workers. The main challenge here was that Gaborone has a lot of hotspots which could not all be visited during the mapping. However, connections were made and the team had a better sense of what would be needed to successfully cover almost of the area during size estimation. The table that follows shows the Greater Gaborone formative assessment outcome.
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Table 2: Greater Gaborone Formative Assessment Conducted
Study Facilitating Classification Attendee Total Assessment Location Entity Composition Participants Type Gaborone DHMT Government Stakeholder Individual KII Gaborone MoHw Government Stakeholder TWG input KII Tlokweng VDC Government Stakeholder Individual KII Gaborone BOFWA Civil Society MSM & FSW Individual KII Gaborone Rainbow Identity Civil Society TG Individual KII Gaborone Nkaikela/RI Civil Society TG & FSW TG*3, FSW *3 FGD
5.1.2.2. Boteti | Ngami | Okavango Some hotels and lodges in Maun were open in admitting to the presence of FSWs on or near their premises. They were not in a position to provide counts but expressed that sex work is somewhat seasonal with the winter season being the high season as this is when tourists come to the area. The sex workers are said to then travel to Gaborone in the other ‘off-season’ times.
FSWs in this location were estimated to be young, generally in their mid-twenties. FSWs who participated in the focus group discussion were generally open about the fact that they were involved in ‘transactional-sex’. In their opinion most ladies seen at bars around the location at night are there specifically to offer sex worker services.
The village of Gumare was found to be rather rural, with less than 3,000 people the DHMT and other service providers (Tebelopele, Social Worker and ACHAP Clinical Staff) found it hard to identify or point research teams to any locations were key populations are found. In their opinion these populations had not come out to seek health services and are as good as non-existent in the village. The team identified seven potential commercial outlets where the public frequent and spent time at these locations on observations however no key populations were identified.
Tebelopele Voluntary Counselling and Testing Centre confirmed servicing FSWs at some point in time, either with counselling or health (treatment) services. The clinic on the other hand confirmed providing services to one transgender person a long time ago but could not say that they had offered services to any FSWs or MSM. The clinic was however clear, the reported number of STIs are on the rise, it is not within their mandate or reporting system to distinguish clients (patients) based on the sexual preference.
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Table 3: Boteti, Ngamiland Formative Assessments Conducted
Study Location Facilitating Classification Key Total Assessment Entity Population Participants Type Letlhakane Tebelopele Civil Society 2*MSM; 6 Focus Group 3*FSW; 1*TG Discussion Letlhakane Tebelopele Civil Society MSM KII Letlhakane Tebelopele Civil Society TG 1 KII agreed and later declined Maun BOFWA Civil Society MSM Peer Outreach Worker Group Meeting Maun BOFWA Civil Society Mixed FSW & 1 Focus Group MSM Discussion Maun BOFWA Civil Society Small Groups 17 Mini Diaries FSW (Individuals & Pairs) Maun BOFWA Civil Society Service 2 Key Informant Provider Maun Radinama Commercial Staff Member 1 Key Informant
5.1.2.3. Palapye | Serowe Participants of the focus group discussion provided useful information on the types of services FSWs render to clients as well as the various platforms they use to garner clients. These platforms include social media, especially Facebook where they form groups to advertise their services. Seed respondents for MSM were identified; in addition to agreeing to be interviewed and partake in focus group discussions, they expressed willingness to help in the Size Estimation component. All the government clinics were visited in Serowe and Palapye where key informant interviews were held. FSW hotspots were successfully mapped and some observations were done at these hotspots where FSWs were identified.
Table 4: Serowe, Palapye Formative Assessments Conducted
Study Facilitating Classification Key Total Assessment Location Entity Population Participants Type Serowe Tebelopele Civil Society MSM & FSW FSW*5 FGD MSM*5 Serowe Kadimo Clinic Government Service Individual KII Provider Serowe Serowe College of Government Service Individual KII Education Provider Serowe Nova Eva Hair Commercial Stakeholder Staff Member KII Saloon Serowe Boipelego Clinic Government Service Individual KII Provider Serowe Nutrition Clinic Government Service Individual KII Provider
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Study Facilitating Classification Key Total Assessment Location Entity Population Participants Type Serowe Serowe Clinic Government Service Individual KII Provider Serowe Newtown Clinic Government Service Individual KII Provider Serowe Mainland Bar Private Stakeholder Individual KII Palapye Tebelopele Civil Society MSM & FSW FSW*5 FGD MSM*5 Palapye Palapye Medical Government Stakeholder Individual KII Centre Palapye Extension 3 Clinic Government General Individual KII Services Palapye BOFWA Civil Society MSM & FSW Individual KII Palapye Palapye Primary Government General Individual KII Hospital Services Palapye Palapye Medical Private General Individual KII Clinic Services Palapye Bokamoso Clinic Private FSW Individual KII
5.1.2.4. Francistown – Tutume The mapping for Francistown/Tutume included the catchment areas of Dukwi, Nata, Mosetse and Sebina. The DHMT served as the point of entry in Francistown. They pointed out that as the Francistown DHMT they are aware of HIV key populations and have measures in place to tackle them. This largely involves working with civil society organisations such as BONELA, BOFWA, Tebelopele and Matselo Community Development Agency (MCDA) to ensure that KPs have access to health services. Tebelopele affirmed that they provide HTC services to MSM and FSW and have a program specifically targeting the mobilization of FSW to access services. MCDA work exclusively with FSWs through provision of condoms and IEC materials in addition to referring them to BOFWA for clinical services. Itekeng Clinic offers services to the general population without necessarily tailoring them to KPs but this is not to say KPs are exempted from services. BOFWA deals mainly with FSW but they do also assist MSM referred to them by LEGABIBO.
FSWs in Francistown were easy to observe in bars and in residential areas. There were additionally a sizeable number of MSM who congregate at particular reveler outlets and were willing to be interviewed with the help of peer outreach workers. In Dukwi the government clinic provides services to the general population and have never experienced a case whereby someone identified as a KP. According to the clinic service providers, “if there are KPs in the village, they are secretive”. A KII however pointed the research team to a few hotspots in the village where FSW could be found and upon checking those places sex work activity was observed.
In Nata a key informant revealed sex work is common practice due to the trucks passing through the place, however they are not open as they do not want to be attached to the practice of sex work. This was echoed by Tebelopele who see a large number of women but none of them admits to sex work.
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Thini S & CD in Tutume do handle cases for MSM, FSW through provision of services like condom distribution and HTC. Tutume Medical Centre also offer services to MSM that include HTC, viral load monitoring and other clinical services. KIIs also offered information on places where MSM congregate and upon visiting the places MSM were indeed observed. The table that follows shows the formative meetings held across the circuit.
Table 5: Greater Francistown Formative Assessments
Study Facilitating Classification Key Total Assessment Location Entity Population Participants Type Francistown Tebelopele Civil Society MSM & FSW Individual KII Francistown MCDA Civil Society FSW Individual KII Francistown Itekeng Clinic Government General Individual KII Services Francistown BOFWA Civil Society MSM & FSW Individual KII Dukwi Dukwi Clinic Government General Individual KII Services Nata Nata Clinic Government General Individual KII Services Nata Tebelopele Civil Society FSW Individual KII Tutume Thini S & CD Clinic Government MSM & FSW Individual KII Tutume Tutume Medical Private MSM Individual KII Centre
5.1.2.5. Kgalagadi North - (Kang & Hukuntsi) In Kgalagadi North meetings were held with government key informants at Kang Clinic, Kang Police, Hukuntsi Hospital, Hukuntsi Clinic and Lehututu Clinic. Information received at Kang Clinic revealed that though they have never treated anyone identifying as MSM, they do observe a high number of STIs in the male populace and in some cases these men do not disclose their STIs to sexual partners. The high number of male STI cases was echoed by an interviewee at Tlhatlogong Private Clinic. The Police were not aware of any stigmatization issues as they never receive such reports and even alluded to knowing a lesbian couple who have been accepted by the community. In a KII at Hukuntsi Clinic it transpired that there is a high number of STI cases amongst women but they could not be attributed to sex work.
Most of the mapped bars in Kang were found to have no FSW activity with the exception of one bar which is said to be the most popular in the village. This bar features a mix of young and old FSW whilst the other bars are said to be frequented by mostly men. A truck stop was also visited but contrary to the expectations of the team there was no more sex activity there taking place due to the management of the adjacent filling station taking issue with the bad reputation of the place as a sex work hub.
The team was able to hold a FGD for MSM in Hukuntsi at a place where they usually congregate. It was a challenge getting the requisite number of participants as the MSM community were said to be having a rivalry. The other challenge in Kgalagadi North was the language barrier as some of the interviewees were not fluent in Setswana and English. The table that follows shows the formative assessments that were held across the circuit.
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Table 6: Kgalagadi North
Study Facilitating Classification Key Total Assessment Location Entity Population Participants Type Kang Kang Clinic Government MSM Individual KII Kang Tlhatlogong Private MSM Individual KII Private Clinic Hukuntsi Hukuntsi Clinic Government MSM Individual KII Hukuntsi Hukuntsi Hospital Government Individual KII Hukuntsi A HE EME (YOHO) Civil Society Individual KII Lehututu Lehututu Clinic Government Individual KII Hukuntsi Setshego Bar Bar MSM & FSW FGD
5.1.2.6. Selebi Phikwe | Chobe The first organizational point of contact in Selebi Phikwe was ‘Silence Kills’, a civil society group. Meetings with this group soon relieved that the season for collecting ‘Mopane Worms’ caterpillar was in season and that many of their members were out working the fields and trading in this highly sought after commodity. This presented a challenge in the linkages to peer outreach workers who were all opting to trade in Mopane at this time. it was anticipated that some of them may return to town in the evening to engage in sex work, which they did, but presented a challenge in the time they had available to meet and recruit other key populations to participate in formative activities.
Formal meetings in Selebi Phikwe were also a challenge, some were successful while several others failed. Successful meetings were held with the District AIDS Coordinator, the DHMT, a key MSM informant at one of the government clinics and at Silence Kills as stated above. Interviews with ‘Good Samaritan, Humana People to People and the intended private medical practitioner was not successful. Notwithstanding the evenings allowed for successful focus group discussions with FSWs and mini MSM interviews. Peer Outreach Workers were also instrumental in mapping hotspots and providing detailed information on KP behavior at various locations. One such anecdote involves a husband and wife team working a street corner where they sell food to a nearby night club while the wife manages a network of younger FSWs and her own clients. This is indicative of the information POW have of the night life and sex trade in their locations. Another anecdote learnt in the mapping exercise is that of a brothel, a home belonging to a former (now late) pastor that is now occupied by grandchildren who are carrying out female sex work. The study team was able to verify and map the site on the ground during the mapping exercise and observe unusual activity around the residence as compared to other households in the neighbourhood.
Table 7: Selebi Phikwe Formative Assessments
Study Facilitating Classification Key Total Assessment Location Entity Population Participants Type Selebi Phikwe PMCFMH Civil Society 10*Mini-MSM Individual KII Selebi Phikwe PMCFMH Civil Society 2*FSW 6 FGDs Selebi Phikwe PMCFMH Civil Society 1*MSM 6 FGDs Selebi Phikwe PMCFMH Civil Society 5 5 KIIs
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5.1.3. Mapping Conclusions Research assistants were able to develop comfort levels and provide in-sight into the practicality associated with or feasibility of the size estimation techniques. The mapping exercise brought about specific recommendations as to how the size estimation was to be approached.
5.2. Size Estimation The size estimation exercise took place exactly one month after the mapping exercise. This was done in order to coincide with the month end period as per the recommendation from the technical working group. The mapping exercise established that service providers do not provide tailor made services that are KP specific, especially where FSWs are concerned. It was established however that service providers can estimate the number of KPs they may have seen using very rough estimates over an extended time frame.
The study protocol provided for the Census Method to be used as an alternative size estimation for FSWs in all the 12 districts. Literature also highlighted the value of using the Enumeration Method which is closely related to the Census Method as a means of improving the size estimate. “Census and enumeration methods boil down, in essence, to counting people. Census methods try to count every individual in a population, for example by visiting every brothel in the country and collecting information on the number of individual sex workers based in each brothel. This has to take place in a very short space of time, since otherwise migration between sites may lead to double counting. Enumeration methods are very similar, but instead of counting every individual they generally start with a sample frame or list, choose a sample of ‘units’ (such as brothels or shooting galleries) from within that list, and count only the individuals within those chosen units. The number counted is then scaled up according to the size and structure of the sample frame. In other words they may count the number of brothels, visit a third of them to get an average number of workers per brothel, and then multiply the average number of workers per brothel by the total number of brothels counted”16. The survey hence acquired additional independent data from Statistics Botswana and local councils to triangulate the findings.
5.2.1. Geographic Scope The six circuits and the number of hotspots identified in each of the circuits are shown in the table that follows.
Table 8: Number of Hotspots by Circuit
Circuit Name Frequency Percent Cum. Percent Boteti - Ngami - Okavango 24 8.54 % 8.54 % Francitown - Tutume - Dukwi - Nata 66 23.49 % 32.03 % Gaborone - - Kweneng West 130 46.26 % 78.29 % Kgalagadi North 8 2.85 % 81.14 % Palapye - - Serowe 12 4.27 % 85.41 % Selebi Phikwe - - Chobe 41 14.59 % 100.00 % TOTAL 281 100.00 % 100.00 %
16 Pisani, E. (2002), Estimating the Size of Populations at Risk, Issues and Methods, Updated July 2003, UNAIDS, Impact, FHI; ISBN 974-91495-0-5
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The highest number of hotspots identified were in the ‘Gaborone - - Kweneng Circuit’ with 130 locations enumerated. This accounts for almost half (46.3%) of the total number of hotspots identified in the entire survey. The least number of hotspots, eight (8), accounting for less than 3% were found in ‘Kgalagadi North Circuit’. The survey circuits were a convenient approach adopted by the study team to physically reach all of the 12 study districts. The districts and number of hotspots reached is shown in the table that follows:
Table 9: Number of Hotspots by District
District Frequency Percent Cum. Percent Boteti 8 2.85 % 2.85 % Chobe 15 5.36 % 8.21% Greater Francistown 61 21.79 % 30.00% Greater Gaborone 122 43.57 % 73.57% Kgalagadi North 8 2.86 % 76.43% Kweneng West 8 2.86 % 79.29% Ngami 8 2.86 % 82.14% Okavango 8 2.86 % 85.00% Palapye 5 1.79 % 86.79% Selebi Phikwe 26 9.29 % 96.07% Serowe 7 2.50 % 98.57% Tutume 4 1.43 % 100.00% TOTAL 280 100.00 % 100.00 %
5.2.2. Key Population Scope The survey focused primarily on linking FSWs to hotspots. The study methodology did not tie the numeration of other Key Populations (KPs), Men who have Sex with Men (MSM), Transgendered People (TGs) and People Who Inject Drugs (PWIDs) to the said hotspots as these are estimated through alternative measures such as the Service Multiplier Method. Notwithstanding, key informants were still asked whether or not the latter three KP groups are ever seen or known to frequent any of the hotspots identified. The table that follows shows that in 225 of the total hotspots no other KPs were observed or known to frequent the venue. MSM where however found to frequent 17.8% of the known FSW hotspots and TGs at less than two percent. PWIDs were not known to frequent these locations at all.
Table 10: Key Informant Perception of KPs who Frequent the Venue
Other KPs Observed Frequency Percent Cum. Percent MSM 50 17.79 % 17.79 % None 225 80.43 % 98.22 % TGs 5 1.78 % 100.00 % TOTAL 280 100.00 % 100.00 %
5.2.3. Female Sex Worker Size Estimates The hotspots that were mapped were visited and efforts made to numerate the FSW population. Two methods were used in the on-sight numeration exercise; first key informants such as establishment staff or peer outreach workers were asked to estimate the ‘least’ and the ‘most’ number of FSWs usually
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 24 seen. Data was also collected from the same ‘hotspot’ establishment owners, workers at the establishment and or independent security personnel who are regularly deployed at the location. These individuals are referred to as key informants offering their best estimate of what they usually observe to be lower and upper estimates of key populations usually seen.
The second approach for the count was through enumeration staff making direct counts of the number of FSWs observed. The research team spent two hours in each hotspot using a specially design enumeration sheet to count the number of FSWs seen. The sheet was designed to capture eight counts at 15 minute intervals over the predetermined two hour periods. These periods where carefully selected based on key informant knowledge of the peak times of the hotspot so as to avoid the limitation of double counting as far as is possible. The field team went to the hotspots at peak hours, defined as days and times in the week when FSWs are more likely to frequent the location. These days and times were informed through community outreach workers and key informants in the mapping stage of the survey.
Hotspots Visited by Day of the Week 100 89 90 80 70 60 60 50 46 38 40 30 20 19 20 9 10 0 Friday, 21st Thursday, Friday, 28th Saturday, Thursday, Friday, 5th Saturday, 27th 29th 4th 6th
Figure 1: Number of Hotspots Visited by Day of the Week
Each hotspot was visited only once. No attempt was made to visit or locate hotspots on Sundays through to Wednesday. The chart above shows a month end spike around the 27th and 28th calendar day. Interesting as this maybe, it is not a direct indicator to the female sex worker availability at this time of the month. Further analysis is required to verify whether the number of sex workers observed follow a similar trend.
The hotspot visits were scheduled at the times recommended by key informants who were knowledgeable of the location and the FSW population in that area. The highest number of hotspots were visited during the eight o’clock evening time slot amounting to 173 hotspots, accounting for 62% of the hotspots visited. We observe from the same graph below that the FSW yield at this time, 8pm is closely related to the number of hotspots visited and the time invested during the 8pm observation. The later 10 pm time however shows a lower yield, 26% against the 32% proportion of hotspots visited. At
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 25 midnight the yield to proportion of hotspots visited is more than double with 4% of the hotspots returning 9.5% of the yield.
Proportion of Time Versus Yield Enumerated (%), n=280 63.5% 65% 62%
55%
45%
35% 32% 26.1% 25%
15% 9.52% 4% 3% 5% 0.4% 0.00% 0.82%
-5% 12am 2am 6pm 8pm 10pm
Proportion of Hotspots FSW Yield
Figure 2: FSW Yield versus time of Enumeration
In addition, the forms collected GPS coordinates of each of the actual locations where the counts were done. This information was used to compile the true mapping locations of each hotspot within metres of each other and reported with global positioning mapping software in the mapping chapter above. Annex # provides a sample copy of the data sheet used to capture the size estimation figures for the survey.
5.2.3.1. Distribution of Hotspots by Health District A total of 280 hotspots were enumerated across the 12 districts. The hotspots identified in each of the Health Districts surveyed show that the highest number of hotspots were identified in the Greater Gaborone area followed by Francistown. Figure 3 below shows that other than the country’s two cities (Gaborone 121 & Francistown 63) the next point of interest is Selebi Phikwe with a total of 26 FSW hotspots. Data from Chobe includes the border crossing location of Kazungula and hotspots in Pandamatenga.
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Distribution of Hotspot Health District 140 121 120
100
80 63 60
40 26 20 15 8 8 8 8 8 5 7 4 0 Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume Francistown Gaborone North West Phikwe
Figure 3: Number of Hotspots per District
5.2.3.2. Hotspot by Town & Village Location A total of thirty-two (32) towns and villages were identified across the 12 districts with FSW hotspots. These include Greater Gaborone and Greater Francistown. Greater Gaborone includes some small almost rural like (peri pre-urban) areas like Metsimotlabe (4), Mmopane (6) and Tloaneng (1), while Greater Francistown includes Mosetse (1), Dukwi (3), Nata (1), Sebina (2), Serule (2) and Tutume (2). Other villages within the districts surveyed where hotspots were located include Ditshegwane (1), Letlhakeng (5), Selajwe (1), and Takatokwane (1) in Kweneng West; Kang (6), Tshane (1), Lekgwabe (1) in Kgalagadi North; Kasane (9), Kazungula (5) and Pandamatenga (1) in Chobe; Shakawe (6) and Mohembo (2) in Okavango; Maun (8) in Ngamiland; Letlhakane (8) in Boteti; and Palapye (5), Selebi Phikwe (26), Serowe (7) in the Central District.
The figure that follows shows all thirty-two (32) locations across which the 280 hotspots have been identified and the number of hotspots in each of the locations.
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Hotspots across Village & Towns (Stratified by GF District) 60
50
40
30 53 54
20
31 26 10 16 8 9 8 8 6 5 7 5 6 6 5 3 4 3
0 1 1 2 1
NATA
KANG
MAUN
DUKWI
SEBINA
SERULE
KASANE
TSHANE
GABANE
SEROWE
PALAPYE
TUTUME
SALAJWE
MOSETSE
SHAKAWE
TLOANENG LEKGWABE
MMOPANE
MODIPANE
MOHEMBO
TLOKWENG
GABORONE
KAZUNGULA
LETLHAKANE
LETLHAKENG
FRANCISTOWN
DITSHEGWANE
SELIBE PHIKWE SELIBE
TAKATOKWANE
MOGODITSHANE
PANDAMATENGA METSIMOTLHABE
Boteti Chobe Greater Francistown Greater Gaborone Kgalagadi North Kweneng West
Ngami Okavango Palapye Selibe Phikwe Serowe Tutume
Figure 4: Hotspot by Location (Village or Town)
5.2.3.3. Hotspot Type by Health District The stacked diagram below shows that bars are the most dominant hotspot type identified across all the districts surveyed. The diagram highlights the dominance of bars as a particular type of hotspot frequented by the FSW population. The figure shows that all outlets in Boteti (8) and Kweneng West (8), Palapye (5) and Serowe (7) are bars. It is important to note that the mapping exercise pointed out other outlet types in these very locations that the survey team followed up in both the mapping and the size estimation activities and found no key populations. As a result, the size estimation does not report numbers of non-active locations.
Figure 5 hence shows that Gaborone has the widest variety of hotspot types. This is anticipated given the size and diversity of the population in the capital city. Greater Francistown, Chobe and Selebi Phikwe also exhibit an interesting variety of hotspot types which include road side pick-up points, lodges patronized by international travels and brothels (hostels).
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Hotspot by Health District
100% 3 1 1 90% 1 80% 70% 60% 50% 8 8 5 7 40% 44 6 19 30% 81 4 4 2 20% 6 10% 0% Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume Francistown Gaborone North West Phikwe
Bar Bar & Club Bar & Depot Bus Stop Club Depot Filling Station Hostel Hotel Liquor Restaurant Lodge Pub Shebeen Street Truck Stop University
Figure 5: Hotspot Type by District
5.2.3.4. FSWs Usually Observed (Least Reported) Staff at hotspots were asked about the least and the most FSW usually seen at their establishments. In some instances, key informants reported that FSWs never patronize their establishments, this despite the knowledge of peer outreach workers who interact closely with FSWs. Of those answering this question, data was collected for both the ‘least’ and the ‘most’ number of FSWs ‘usually seen’ in all of the twelve districts. The table that follows provides a column of the numbers offered by respondents as the ‘Least Usually Seen’ against the frequency with which that number was stated across all the sites. The data shows that 13.0% (24) of those responding (184) to the question said that there is usually zero FSWs seen at the location. The data also shows that 14.7% (27) of those responding to this question estimated that at least 10 FSWs are often seen at their location or hotspot. Similarly, one respondent out of the 184 said that the least number of FSWs observed is 55.
Table 11: Least Number of Female Sex Workers Usually Seen
Least Usually Seen Frequency Percent Cum. Percent 0 24 13.04 % 13.04 % 1 14 7.61 % 20.65 % 2 11 5.98 % 26.63 % 3 15 8.15 % 34.78 % 4 11 5.98 % 40.76 % 5 32 17.39 % 58.15 % 6 9 4.89 % 63.04 % 7 4 2.17 % 65.22 % 8 6 3.26 % 68.48 % 9 6 3.26 % 71.74 % 10 27 14.67 % 86.41 % 11 1 0.54 % 86.96 % 12 1 0.54 % 87.50 % 14 1 0.54 % 88.04 %
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Least Usually Seen Frequency Percent Cum. Percent 15 7 3.80 % 91.85 % 17 1 0.54 % 92.39 % 20 8 4.35 % 96.74 % 25 1 0.54 % 97.28 % 30 2 1.09 % 98.37 % 35 1 0.54 % 98.91 % 40 1 0.54 % 99.46 % 55 1 0.54 % 100.00 % TOTAL 184 100.00 % 100.00 %
The graph that follows provides an aggregated distribution of the least number of FSWs usually seen at the district level. All the districts except for Serowe report a minimum number of FSWs usually seen. The data shows that 844 FSWs are estimated as the ‘least usually seen’ for the Greater Gaborone District, Greater Francistown estimated 180 FSWs and Selebi Phikwe estimated 149.
Least Number of FSWs Reported as 'Usually Seen' 900 844 800 700 600 500 400 300 180 200 149 100 39 7 3 4 10 9 25 0 3 0 Boteti Chobe Greater Greater Kgalagadi Kweneng Ngamiland Okavango Palapye Selebi Serowe Tutume Francistown Gaborone North West Phikwe
Figure 6: Least Number of Female Sex Workers Estimated as Usually Seen by District Informants
Table 12 below shows the overall distribution of the least number of FSWs usually seen as reported across the twelve districts. The data shows informants at six (6) hotspot venues in Greater Francistown, eight (8) Gaborone, one (1) in Kgalagadi North, four (4) in Kweneng West, four (4) in Selebi Phikwe and one (1) in Tutume say they usually do not observe any FSWs in their place of business or work. For those who said five was the ‘least usually seen’, 3 were in Boteti, 7 in Greater Francistown, 16 in Greater Gaborone, and 6 in Selebi Phikwe. Two hotspots in Gaborone said the lowest number of FSW usually seen is 30 while one said their lowest number is 40 and another said 55 was the lowest usually seen.
At the district level (figure 6 & table 12) it is therefore observed from the data that the least number of FSWs seen in Boteti 39, in Chobe the estimate was 7 and in Greater Gaborone this estimate was 844.
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Table 12: Distribution of Least Number of Female Sex Workers Usually Seen by District
Least Usually Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selebi Serowe Tutume TOTAL Seen Francistown Gaborone North West Phikwe 0 0 0 6 8 1 4 0 0 0 4 0 1 24 1 1 1 4 2 1 1 0 0 0 1 0 3 14 2 0 1 3 3 1 0 2 0 0 1 0 0 11 3 1 0 3 7 0 1 2 0 0 1 0 0 15 4 1 1 2 6 0 0 0 0 0 1 0 0 11 5 3 0 7 16 0 0 0 0 0 6 0 0 32 6 0 0 1 7 0 0 0 0 1 0 0 0 9 7 0 0 1 3 0 0 0 0 0 0 0 0 4 8 2 0 0 4 0 0 0 0 0 0 0 0 6 9 0 0 0 3 0 0 0 1 1 1 0 0 6 10 0 0 9 12 0 0 0 0 1 5 0 0 27 11 0 0 0 1 0 0 0 0 0 0 0 0 1 12 0 0 0 1 0 0 0 0 0 0 0 0 1 14 0 0 0 1 0 0 0 0 0 0 0 0 1 15 0 0 1 4 0 0 0 0 0 2 0 0 7 17 0 0 0 1 0 0 0 0 0 0 0 0 1 20 0 0 0 7 0 0 0 0 0 1 0 0 8 25 0 0 0 1 0 0 0 0 0 0 0 0 1 30 0 0 0 2 0 0 0 0 0 0 0 0 2 35 0 0 0 1 0 0 0 0 0 0 0 0 1 40 0 0 0 1 0 0 0 0 0 0 0 0 1 55 0 0 0 1 0 0 0 0 0 0 0 0 1 TOTAL 8 3 37 92 3 6 4 1 3 23 0 4 184 SUMMATION 39 7 180 844 3 4 10 9 25 149 0 3 1273
5.2.3.5. FSWs Usually Observed (Most Reported) Key informants and staff were also asked the ‘highest number’ of FSWs usually seen at their establishment or business location. Table 13 shows that of the 180 individuals who responded to the question, 8 respondents estimated that the highest number of FSWs usually seen at their establishment was three (3). This accounted for 4.44% of those answering the ‘most usually seen’ question. The frequency table that follows gives the complete distribution of the ‘most usually seen’ with 75 FSWs being reported to be the usual maximum at two locations.
Table 13: Most Number of Female Sex Workers Usually Seen
Most Usually Seen Frequency Percent Cum. Percent 2 1 0.56 % 0.56 % 3 8 4.44 % 5.00 % 4 6 3.33 % 8.33 % 5 20 11.11 % 19.44 % 6 2 1.11 % 20.56 % 7 2 1.11 % 21.67 % 8 5 2.78 % 24.44 % 9 2 1.11 % 25.56 % 10 32 17.78 % 43.33 % 11 2 1.11 % 44.44 % 12 7 3.89 % 48.33 % 13 1 0.56 % 48.89 % 14 1 0.56 % 49.44 % 15 12 6.67 % 56.11 % 16 1 0.56 % 56.67 %
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Most Usually Seen Frequency Percent Cum. Percent 17 2 1.11 % 57.78 % 18 1 0.56 % 58.33 % 20 16 8.89 % 67.22 % 21 1 0.56 % 67.78 % 25 7 3.89 % 71.67 % 30 17 9.44 % 81.11 % 31 1 0.56 % 81.67 % 35 5 2.78 % 84.44 % 37 1 0.56 % 85.00 % 40 9 5.00 % 90.00 % 42 1 0.56 % 90.56 % 45 1 0.56 % 91.11 % 48 2 1.11 % 92.22 % 50 7 3.89 % 96.11 % 60 2 1.11 % 97.22 % 66 1 0.56 % 97.78 % 70 1 0.56 % 98.33 % 74 1 0.56 % 98.89 % 75 2 1.11 % 100.00 % TOTAL 180 100.00 % 100.00 %
The graph that follows provides an aggregated distribution of the most number of FSWs usually seen at the district level. Serowe did not report a maximum number of FSWs usually seen and Okavango had no variation between the least and most. The data shows that highest number of FSWs usually seen was reported in the Greater Gaborone area (2339), the next highest was reported in Greater Francistown (575) followed by Selebi Phikwe with 441.
Most Number of FSWs Reported as 'Usually Seen' 2500 2339
2000
1500
1000 575 441 500
71 26 8 50 28 9 28 0 11 0 Boteti Chobe Greater Greater Kgalagadi Kweneng Ngamiland Okavango Palapye Selebi Serowe Tutume Francistown Gaborone North West Phikwe
Figure 7: Most Number of Female Sex Workers Usually Seen by District
Table 14 below shows the overall distribution of the most number of FSWs ‘usually seen’ as reported across the twelve districts by 180 informants. The data shows that six venue respondents in Kweneng West responded to the ‘most usually seen’ question. Of these, respondents at one location reported that 2 is the highest number of FSWs usually seen at their venue. Still in Kweneng West two locations
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estimate 5 as the most usually seen, one estimates 8, one estimates 10, and another estimated that the most usually seen is 20. Data from the six locations in Kweneng West bring the district total estimate of FSWs, ‘most usually seen’ to 50. The total estimate for ‘most usually seen’ across all twelve survey districts is also presented in the table.
Table 14: Distribution of Most Female Sex Workers Usually Seen by District
Most Usually Greater Greater Kgalagadi Kweneng Selebi Boteti Chobe Ngami Okavango Palapye Serowe Tutume TOTAL Seen Francistown Gaborone North West Phikwe 2 0 0 0 0 0 1 0 0 0 0 0 0 1 3 0 0 2 2 1 0 0 0 1 0 0 2 8 4 0 1 3 1 0 0 0 0 0 1 0 0 6 5 1 0 6 5 1 2 2 0 1 1 0 1 20 6 0 0 0 2 0 0 0 0 0 0 0 0 2 7 1 0 0 0 0 0 0 0 0 1 0 0 2 8 1 0 0 2 0 1 1 0 0 0 0 0 5 9 1 0 0 1 0 0 0 0 0 0 0 0 2 10 3 1 10 10 0 1 1 0 0 6 0 0 32 11 0 0 0 2 0 0 0 0 0 0 0 0 2 12 1 1 1 3 0 0 0 0 0 1 0 0 7 13 0 0 0 1 0 0 0 0 0 0 0 0 1 14 0 0 0 1 0 0 0 0 0 0 0 0 1 15 0 0 3 9 0 0 0 0 0 0 0 0 12 16 0 0 0 1 0 0 0 0 0 0 0 0 1 17 0 0 0 2 0 0 0 0 0 0 0 0 2 18 0 0 0 0 0 0 0 0 0 1 0 0 1 20 0 0 1 9 0 1 0 0 1 4 0 0 16 21 0 0 0 1 0 0 0 0 0 0 0 0 1 25 0 0 0 7 0 0 0 0 0 0 0 0 7 30 0 0 5 8 0 0 0 0 0 4 0 0 17 31 0 0 0 1 0 0 0 0 0 0 0 0 1 35 0 0 0 4 0 0 0 0 0 1 0 0 5 37 0 0 0 1 0 0 0 0 0 0 0 0 1 40 0 0 5 4 0 0 0 0 0 0 0 0 9 42 0 0 0 1 0 0 0 0 0 0 0 0 1 45 0 0 0 1 0 0 0 0 0 0 0 0 1 48 0 0 0 2 0 0 0 0 0 0 0 0 2 50 0 0 0 5 0 0 0 0 0 2 0 0 7 60 0 0 0 2 0 0 0 0 0 0 0 0 2 66 0 0 0 1 0 0 0 0 0 0 0 0 1 70 0 0 0 1 0 0 0 0 0 0 0 0 1 74 0 0 0 1 0 0 0 0 0 0 0 0 1 75 0 0 0 2 0 0 0 0 0 0 0 0 2 TOTAL 8 3 36 93 2 6 4 0 3 22 0 3 180 SUMMATION 71 26 575 2339 8 50 28 0 28 441 0 11 3577
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5.2.3.6. Lowest and Highest Comparative Observations The aggregate difference between the least and the most FSWs usually seen in the 12 district is particularly significant in the major population centres. Figure 8 below shows that the three centres with the highest estimates, Gaborone, Francistown and Selebi Phikwe report large differences between the least and the most usually seen. The survey protocol based on numerous studies determined that the higher of these two numbers should be used as an input variable to the final calculation. This is so due to the hidden nature of FSW populations even to the trained eye attempting to make an estimate observation.
Distribution of FSWs Usually Seen by District
2500 2339
2000
1500
1000 844
575 441 500 180 149 71 39 7 26 3 8 4 50 10 28 9 0 25 28 0 0 3 11 0 Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selebi Phikwe Serowe Tutume Francistown Gaborone North West
Least Usually Most Usually
Figure 8: Comparison of Least and Most Female Sex Workers Usually Seen by District.
5.2.3.7. FSWs Directly Observed In addition to gaining informant insights about the number and presence of key populations at venues, the third technique for size estimation was that of direct observation. This allowed to a three-point verification of data between the least usually seen, the most usually seen and the directly observed.
In conducting the directly observed census enumeration, the research teams spent two hours at each of the 280 hotspots in order to directly count (numerate) the number of FSWs seen. There teams followed a four stage count per hour making a total of eight counts across a two-hour period. The teams spaced out these counts at equal intervals starting from ‘the top of the hour’. The top of the hour was defined as either 8 pm (20h00), 10 pm (22h00) or midnight, 12 am. In hotspot venues where 8pm was
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determined to be the start time for ‘peak’ activity the team enumerator remained at that location for the period 8 pm to 10 pm. The enumerator at this location took a count at 8:00 pm, 8:15 pm, 8:30 pm, 8:45 pm, 9:00 pm, 9:15 pm, 9:30 and 9:45 pm. This implies a total number of eight counts for all such locations. This system of numerating was maintained for the 10 pm and the midnight counts. Figure 9 shows the distribution of these counts according to the time of day.
Time of Hotspot Enumeration, n=280 70% 62% 60%
50%
40% 32% 30%
20%
10% 4% 0.4% 3% 0% 12am 2am 6pm 8pm 10pm
Figure 9: Distribution of Actual Time of Day of Directly Observed Census Numeration
Table 15 provides a distribution of the final directly observed estimate for FSWs across each of the 12 districts.
Table 15: Number of Female Sex Workers Directly Observed by District
Max Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selebi Serowe Tutume TOTAL Francistown Gaborone North West Phikwe 0 0 2 9 15 2 2 0 2 0 3 1 2 38 1 0 1 3 5 2 0 0 0 0 3 0 2 17 2 4 1 7 7 0 2 0 0 0 1 2 0 24 3 1 2 5 9 1 0 1 1 0 2 0 0 22 4 3 0 4 6 0 2 2 0 0 0 1 0 18 5 0 0 2 8 0 1 1 0 0 1 0 0 13 6 0 1 1 3 1 0 0 1 1 2 0 0 10 7 0 0 5 11 0 0 1 0 0 1 0 0 18 8 0 1 2 4 0 0 0 1 0 0 0 0 8 9 0 0 0 4 1 1 0 1 0 0 0 0 7 10 0 0 1 6 0 0 0 0 1 0 0 0 8 11 0 0 0 1 0 0 0 1 0 1 2 0 5 12 0 0 6 2 0 0 0 0 0 1 0 0 9 13 0 0 1 2 0 0 0 1 0 0 0 0 4 14 0 0 1 0 0 0 0 0 0 0 0 0 1 15 0 0 1 3 0 0 0 0 0 1 1 0 6 16 0 0 1 1 0 0 1 0 0 3 0 0 6
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Max Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selebi Serowe Tutume TOTAL Francistown Gaborone North West Phikwe 17 0 0 0 2 0 0 0 0 0 0 0 0 2 18 0 0 0 0 0 0 0 0 1 2 0 0 3 20 0 0 0 2 0 0 0 0 1 1 0 0 4 21 0 0 0 4 0 0 0 0 0 0 0 0 4 22 0 1 0 3 0 0 0 0 1 0 0 0 5 24 0 0 0 3 0 0 0 0 0 1 0 0 4 25 0 0 5 2 0 0 0 0 0 1 0 0 8 26 0 0 0 1 0 0 0 0 0 1 0 0 2 27 0 0 0 1 0 0 0 0 0 0 0 0 1 28 0 0 0 3 0 0 0 0 0 0 0 0 3 30 0 0 0 1 0 0 0 0 0 0 0 0 1 31 0 0 1 1 0 0 0 0 0 0 0 0 2 32 0 0 1 1 0 0 0 0 0 0 0 0 2 33 0 0 0 1 0 0 0 0 0 0 0 0 1 34 0 0 0 2 0 0 0 0 0 0 0 0 2 35 0 0 3 1 1 0 0 0 0 1 0 0 6 39 0 0 0 1 0 0 0 0 0 0 0 0 1 41 0 0 0 1 0 0 0 0 0 0 0 0 1 43 0 0 1 0 0 0 0 0 0 0 0 0 1 44 0 0 0 1 0 0 0 0 0 0 0 0 1 45 0 1 0 0 0 0 0 0 0 0 0 0 1 47 0 0 0 1 0 0 0 0 0 0 0 0 1 48 0 0 0 1 0 0 0 0 0 0 0 0 1 49 0 1 0 0 0 0 0 0 0 0 0 0 1 50 0 1 0 0 0 0 0 0 0 0 0 0 1 53 0 0 0 1 0 0 1 0 0 0 0 0 2 55 0 0 0 1 0 0 0 0 0 0 0 0 1 56 0 1 0 0 0 0 0 0 0 0 0 0 1 58 0 1 0 0 0 0 0 0 0 0 0 0 1 89 0 0 0 0 0 0 1 0 0 0 0 0 1 91 0 1 0 0 0 0 0 0 0 0 0 0 1 96 0 0 1 0 0 0 0 0 0 0 0 0 1 Total 8 15 61 122 8 8 8 8 5 26 7 4 280 MAX 23 394 687 1494 55 26 181 50 76 287 45 2 3320 AGGREGATE
Map 1 shows the distribution of the 122 hotspot venues across the Greater Gaborone area (from Metsimotlhabe to Tlokweng). An area of venue types that include night clubs, hotels, motels, shebeens which are unlicensed venues, as well as hostel (brothel type operations) and street locations can be observed from this map.
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Map 1: Distribution of Key Populations across Greater Gaborone
Map 2 presents a geographical illustration of 53 venues where Key Population members were observed in central Gaborone. This is a subset of the ‘Greater Gaborone’ 122 hotspot venues which are shown in the Gabane, Tlokweng, Mogoditshane maps.
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Map 2: Distribution of KPs across Central Gaborone
It is also observed from the maps that female sex workers are present in all the locations while MSM and TGs, are present but in far fewer locations. Map 3 and Map 4 provide a closer view of Mogoditshane and Tlokweng, both location are located on the periphery of the capital and form part of Greater Gaborone.
It is interesting to note the identification of MSM in Mogoditshane (Map 3) as it is technically (administratively) outside of Gaborone and falls under the Kweneng administration which is rural or per- urban. This helps to provide an insight into the social dynamic changes that are extended beyond the confines of the city.
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Map 3: Distribution of Key Population across Mogoditshane
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Map 4: Distribution of Key Populations across Tlokweng
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5.2.3.8. Directly Observed Yield (Peak Days) Key informants in this survey and literature from other studies suggest that weekends, month ends and days or periods just before these have been found to be ‘high yield’ times for locating key populations. The graph (figure 10) that follows shows the distribution of the days of the week from whence the 280 hotspot venues were visited for the direct observation. The highest number of hotspots were visited on Fridays (144) followed by 98 visited on Thursdays.
Hotspots Visited by Day of the Week
160 144 140
120 98 100
80
60 38 40
20
0 Thursdays Fridays Saturdays
Figure 10: Hotspot Venue Data Collection Visits by Day of the Week
The data presented thus far in, figure 10, implies that Thursdays and Fridays were the most visited days and that 8pm (figure 9) was the time slot most visited followed by 10pm. The data also shows that Saturdays, Sundays and other time slots as early as 4pm and as late as mid-night and 2am were also included in the attempted times to directly observe key populations. Regardless of these attempts, the FSW yield largely followed the advice and suggestions provided by stakeholders, key informants and the documented literature with almost 90% of the yield being observed from 8pm up to midnight (figure 11).
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Yield by the Hour (%) 70.00% 63.5% 60.00% 50.00% 40.00% 30.00% 26.1% 20.00% 9.52% 10.00% 0.82% 0.00% 0.00% 12am 2am 6pm 8pm 10pm
Figure 11: FSW Yield per Hour
5.2.3.9. Average Yield per Hotspot
Figure 12 shows an average yield of FSW per hotspot district with Chobe showing the highest average yield. Table 9 above provides a distribution of hotspots across all the districts where a total of 15 hotspots were identified in the Chobe district from which a FSW yield of 394 was directly observed. Similarly, a total of 8 hotspots were identified in Ngamiland District for a direct count of 181 FSWs. The simple average shows that hotspots in Chobe and in Ngamiland have a cumulative average of 26 and 23 FSW respectively.
The graph further shows that, while Gaborone, Francistown and Selebi-Phikwe have high direct FSW yields, the number of hotspots in these districts are also high resulting in a lower yield of FSW per hotspot for each of these locations, Greater Gaborone (12), Greater Francistown (11) and Selebi-Phikwe (11).
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FSW Average Hotspot Venue Yield by District
30 1494 1600
26 1400
25
23 1200 20 1000
15 15 800 687 12 11 11 600 10 394 7 400 6 Maximum Directly Observed 287 6 5 181 3 200 76 55 3 Average Number of FSW Average FSW of perNumberVenue Hotspot 45 50 26 23 2 0 1 0 Chobe Ngami Palapye Greater Greater Selebi Kgalagadi Serowe Okavango Kweneng Boteti Tutume Gaborone Francistown Phikwe North West Axis Title
Max Observed Average Yield
Figure 12: Average FSW Hotspot Yield by District
The data in table 16 below provides specifics in relation to hotspot type and time of day. We are able to see that ‘M Bar’ in Francistown was the highest directly observed number of FSWs recorded during the 10 pm to 12 midnight count. The next highest count was in the car part outside ‘T’s Night Club’ near the Kazungula border post with 91 FSWs counts in the post mid-night counting cycle. It must be noted that a simultaneous count took place inside the night club which found estimated a count of 58 FSWs. In addition, Sisheke Bar (about one kilometer away) reaped 56 FSWs during the 8pm count. Map provides a geographical display of the Chobe district.
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Map 5: Key Population Presence in Chobe District
‘F-Exec’ night club in Maun (tourist location) had an estimate of 89 FSWs directly observed during the ‘after midnight’ count. Of interest, both Moremogolo and Pakatsotlhe are also located close to border crossings popular with long distance travel, the former being at Kazungulu enroute to Zambia and the latter at Tlokweng enroute to South Africa. All the peak time recorded at after 8 pm.
Table 16: Selected Data of Most Frequented Hotspots (Top Twenty)
Count Time Date Data Collected Unadjusted Max Hotspot Name Hotspot Type Town
10:00:00 PM Thursday, May 04, 2017 96 M Bar FRANCISTOWN 12:00:00 AM Friday, April 28, 2017 91 T (CAR PARK) Club KAZUNGULA 12:00:00 AM Saturday, April 29, 2017 89 F- EXEC Club MAUN 12:00:00 AM Friday, April 28, 2017 58 T Club (INSIDE) Club KAZUNGULA 8:00:00 PM Friday, April 28, 2017 56 S-S-H Bar KAZUNGULA 8:00:00 PM Friday, April 21, 2017 55 P-K Bar & Depot TLOKWENG 10:00:00 PM Thursday, April 27, 2017 53 AV Hotel GABORONE 8:00:00 PM Friday, April 28, 2017 53 24/7 Bar MAUN 8:00:00 PM Saturday, April 29, 2017 50 M Lodge KASANE 8:00:00 PM Friday, April 28, 2017 49 M Liquor Restaurant KAZUNGULA
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Count Time Date Data Collected Unadjusted Max Hotspot Name Hotspot Type Town
8:00:00 PM Thursday, April 27, 2017 48 D - C Bar GABORONE 10:00:00 PM Thursday, April 27, 2017 47 C Lounge GABORONE 8:00:00 PM Friday, April 28, 2017 45 CH Bar KASANE 8:00:00 PM Thursday, April 27, 2017 44 EXT-F Bar GABORONE 8:30:00 PM Saturday, May 06, 2017 43 MOT Bar FRANCISTOWN 10:00:00 PM Thursday, April 27, 2017 41 G Hotel GABORONE 11:00:00 PM Friday, April 21, 2017 39 Z Club GABORONE 8:00:00 PM Friday, May 05, 2017 35 EX-C- S Bar FRANCISTOWN 8:00:00 PM Friday, May 05, 2017 35 B SPORT Bar FRANCISTOWN 8:00:00 PM Friday, May 05, 2017 35 P Bar FRANCISTOWN
The maps that follow offer a comprehensive geographical presentation of the locations of all the hotspots in the remaining health districts that were surveyed throughout this size estimation exercise. The legends provide detail around the intensity and presence of various key population groups in each of the districts.
Map 6 shows the vast spread and sparely populated layout of the Greater Francistown health district. The health district includes Serule to the south and Dukwi to the west. The presence of Trans-gender people is noted in all the locations in the district aside from Serule.
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Map 6: Presence of Key Population Groups across Greater Francistown
Francistown Central in Map 6 below shows a more populated picture than the broader district. The hotspot venue with the highest directly observed estimate is found between the water treatment plant and Maradu Primary School on this map. The proximity of Francistown to Zimbabwe and the historical mining town of Selebi-Phikwe are some of the socio-economic dynamics that contribute to the high presence of FSW in the city. The absence of trans-gendered people within the city limits is a point of interest for more detailed study.
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Map 7: Presence of Key Population Groups in Central Francistown
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Map 8 shows the Okavango District which sits in the far North-west corner of Botswana bordering Namibia. The map shows numerous settlements where no KPs were located as well as a military base camp. We also observe several border crossings in this district.
Map 8: Female Sex Worker Intensity in Okavango District
Map 9 provides an insight into the Ngamiland District. The town of Maun, often referred to as the tourism capital, is situated in the heart of this district. International flight connections and a well- established lodge and hotel sector positions Maun as the gateway to the Okavango which lies in the adjacent district.
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Map 9: Female Sex Worker Intensity in Ngamiland
The Boteti Sub-district is shown in Map 10. This district houses one of the largest diamond mines in the country. Access into the mine, which comprises the town of Orapa requires an entry permit. The survey instead focused on the areas that were less restrictive to the public entry. We hence see venues around the nearby town of Lethlakane where workers are known to go for recreation and recuperation. It is worth noting that the mine hospital supports the provision of health services primarily to the mining community. The general public can however be referred to this facility in cases where government facilities do not have the resources and equipment that the mine facility has.
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Map 10: Female Sex Worker Presence in Boteti Sub-district
The Central District is represented in the survey by Palapye and Serowe, shown in map 11. These are peri-urban locations which maintain a village demeanor. In the case of Palapye the International University of Science and Technology and the power station has drastically changed the development status of the region. Twelve venues were identified between these two locations with FSW intensity as shown in the map.
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Map 11: Female Sex Worker Key Population intensity in the Central District
The mining town of Selebi-Phikwe presented a wider array of hotspot venue types than those in Palapye and Serowe. One of the more interesting venues were found here classified as a hostel. There is also an intensity variation that can be observed from this map, some locations had no FSW observed at all and others had above 25 workers spotted as described by the legend.
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Map 12: Female Sex Worker Intensity in Selebi-Phikwe
Tutume sub-district covers a widespread geographic area reaching as far as Sebina, Dukwi, Nata and Gweta. The truck stop at Nata is one of the locations with a mobile population. The study identified a host of dynamics where mobile populations are concerned and the use of mobile telephone applications which make it hard for KPs to be identified.
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Map 13: Tutume Female Sex Worker Intensity
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5.2.4. Sex Worker Diaries
5.2.4.1. District Distribution A small sample of eighty Female Sex Workers who were extremely comfortable were selected and asked six basic questions related to their work. This was in an effort to gain a general sense of some of the dynamics that this key population group experience in their daily activities. The distribution of where the sample was drawn from is shown in the table below to have come from seven of the health districts. Greater Francistown accounted for 40% of the respondents while 28.8% came from Greater Gaborone and 12.5% from Selebi Phikwe.
Table 17: Number of Sex Workers Interviewed by District
GF District Frequency Percent Cum. Percent Boteti 1 1.25 % 1.25 % Chobe 5 6.25 % 7.50 % Greater Francistown 32 40.00 % 47.50 % Greater Gaborone 23 28.75 % 76.25 % Palapye 6 7.50 % 83.75 % Selebi Phikwe 10 12.50 % 96.25 % Serowe 3 3.75 % 100.00 % TOTAL 80 100.00 % 100.00 %
5.2.4.2. Age Range Sex workers were asked what they knew about the age range of fellow sex workers; they were asked to estimate based on their knowledge and their own age what they felt the age of most sex workers in their network is. They disclosed a wide range from as young as 14 years old to 38 years. The ranges described here are as narrated by FSWs, unweighted and unadjusted, the graph displays the minimum age in the range given. Figure 13 shows a spike where the bulk (48%) of the age ranges given start at 18 years to 20 years with a good number also appearing with a 25 year range minimum. Thereafter the numbers fall indicating that by age 30 most FSWs move out of active trade. It is valuable to note that while the study defined FSW as those from age 16 upward, a small number of network members revealed knowledge of colleagues aged 14 years.
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Minimum Age in Range (with Percent) 16 25% 15
14 20% 19% 12 12
10 10 16% 15% 8 8 13%
10% 10% 6 5 4 4 4 6% 3 3 5% 5% 5% 2 2 4% 2 2 4% 2 2 3% 3% 1 1 3% 3% 1 3% 1% 1% 1% 0 0% 14 15 16 17 18 19 20 21 22 23 24 25 26 27 29 30 36 TOTAL Percent
Figure 13: Estimated Age Range of Female Sex Workers
5.2.4.3. The Nationalities Female Sex Workers were asked what they thought the nationality of most female sex workers was in and around the area where they worked. The majority, almost half (48.75%), thought that their fellow sex workers were local (Batswana). An additional number (27.5%) thought that female sex workers were either local or from Zimbabwe. The only other nationality named by sex workers that may be working in the surveyed areas was Zambian.
Table 18: Female Sex Worker's Perception of Nationality of other Female Sex Workers
PERCEIVED NATIONALITY OF FSWs Frequency Percent Cum. Percent Batswana 39 48.75 % 48.75 % Batswana and Zimbabweans 1 1.25 % 50.00 % Batswana and Namibians 1 1.25 % 51.25 % Batswana and Zambians 1 1.25 % 52.50 % Batswana and Zimbabweans 22 27.50 % 80.00 % Batswana, Zambians and Zimbabweans 2 2.50 % 82.50 % Batswana. Zambians and Zimbabweans 1 1.25 % 83.75 % Most of them are foreigners 1 1.25 % 85.00 % Zambians and Zimbabweans 1 1.25 % 86.25 % Zimbabweans 11 13.75 % 100.00 % TOTAL 80 100.00 % 100.00 %
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5.2.4.4. Clientele Serviced FSWs were asked how many clients they would see on a ‘good business day’. Nineteen respondents (FSWs) said that they could see five clients ‘on a good day’. The bulk of respondents see between 5 and 8 clients a day when business is good.
Table 19: Estimating Number of Clients on a 'Good Business Day'
Number of Clients Frequency Percent Cum. Percent 1 1 1.25 % 1.25 % 2 7 8.75 % 10.00 % 3 10 12.50 % 22.50 % 4 4 5.00 % 27.50 % 5 19 23.75 % 51.25 % 6 10 12.50 % 63.75 % 7 13 16.25 % 80.00 % 8 8 10.00 % 90.00 % 10 5 6.25 % 96.25 % 15 1 1.25 % 97.50 % 99 2 2.50 % 100.00 % TOTAL 80 100.00 % 100.00 %
On a bad business day FSWs go without meeting any client, nine respondents expressed this reality. Most other respondents can see between one (45%) and two (26.25%) clients on a bad day.
Table 20: Estimated Number of Clients on a 'Bad Business Day'
Number of Clients Frequency Percent Cum. Percent 0 9 11.25 % 11.25 % 1 36 45.00 % 56.25 % 2 21 26.25 % 82.50 % 3 8 10.00 % 92.50 % 4 2 2.50 % 95.00 % 5 2 2.50 % 97.50 % 99 2 2.50 % 100.00 % TOTAL 80 100.00 % 100.00 %
5.2.4.5. Service Pricing Pricing for commercial sex varies from as little as P20. Alcohol is also accepted as a tradeoff for commercial sex services. FSWs determine pricing based on time frames, often referred to as short time or for the night. The number of sexual rounds is another price determining factor named by the workers interviewed as the number of rounds has time implications and as seen in the figure 14 below, time is a major cost determining factor by 29.1% of respondents followed by the use or non-use of condoms by 23.6% of the respondents.
Each point on the scatter gram relates to the price charged by all of the respondents. Four respondents said that said they charge P20 as a minimum base or average price while two revealed that their minimum charge is P500. The trend line indicators that the minimum price range for those interviewed averages from P50 to around P120.
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Base Price (Min/Average) P600.00
P500.00
P500.00
P400.00
P300.00
P200.00 Price Stated in BwP in Stated Price P100.00 P70.00 P50.00 P20.00 P20.00 P20.00 P20.00 P0.00 0 10 20 30 40 50 60 70 80 90
Individual Respondents Figure 14: Minimum Average Price for Commercial Sex Services
Similarly figure 15 provides an overall scatter diagram of the maximum price FSWs say they charge for their services. The maximum trend line shows upper end pricing that ranges from P250 to P300. This pricing is more closely associated with the ‘long time’ description, where a FSW could spend the night with a client as opposed to ‘short-time’ that is associated with the number of sexual encounters (rounds) and the lower pricing as shown in Figure 14.
Price (Maximum) P1,200.00
P1,000.00
P1,000.00
P800.00
P600.00 P500.00
P400.00
Price Price Stated in Pula P300.00 P250.00 P300.00 P200.00 P30.00 P0.00 0 10 20 30 40 50 60 70 80 90 Individual Respondents
Figure 15: Maximum Price Charged for Commercial Sex Services
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The two tables (table 22 and table 23) show specific elements of the minimum and the maximum prices charged by those FSWs who were willing to provide information about how much they charge for their services. A number of those who offered minimum pricing also said that that was just the average price that they charged for their services. Seventy-four individuals of the 80 interviewed where happy to give information about their minimum price while only forty-six revealed their maximum fee.
Table 21: Minimum Service Pricing for Female Sex Work Services
Base Price in Pula Price Frequency Percent Cum. (Min/Average) Percent 20 4 5.41% 5.41% 30 7 9.46% 14.86% 40 1 1.35% 16.22% 50 27 36.49% 52.70% 60 2 2.70% 55.41% 70 6 8.11% 63.51% 100 10 13.51% 77.03% 120 1 1.35% 78.38% 150 3 4.05% 82.43% 200 7 9.46% 91.89% 250 2 2.70% 94.59% 300 2 2.70% 97.30% 500 2 2.70% 100.00% TOTAL 74 100.00% 100.00%
Table 22: Maximum Service Pricing for Female Sex Work Services
Maximum Price in Pula Frequency Percent Cum. Percent 30 2 4.35% 4.35% 50 2 4.35% 8.70% 80 1 2.17% 10.87% 100 3 6.52% 17.39% 150 1 2.17% 19.57% 200 14 30.43% 50.00% 250 4 8.70% 58.70% 300 10 21.74% 80.43% 350 1 2.17% 82.61% 500 6 13.04% 95.65% 1000 2 4.35% 100.00% TOTAL 46 100.00% 100.00%
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5.2.4.6. Factors that Influence Pricing The Sex Worker Diaries show that ‘time and money’ are the major influences in their work. A Sex Workers perception of what she thinks a client can pay is what she will choose to charge. This is called ‘Financial Status’. A client’s financial status can either be known due to past payment for services or is could be perceived by the sex worker cased on the client’s appearance and presentation, that is the car one drives or the way you are dressed. A smaller number of Sex Workers also feel that nationality is a factor to consider when setting the price, they charge.
The time taken with a client is also a major determinant in price setting. The sexual activities or styles and positions have an effect on the time that workers spend with their clients and therefore affects the price they charge. A Female Sex Worker’s level of need, and the time of the month are also factors that determine the price charged. Demand for sex at the end of the month is high because of the ‘pay-day phenomenon’, sex workers know that the willingness to pay is high and hence they can charge a higher price. Notwithstanding the mapping component of the survey did identify sex workers who had regular clients that they offered serviced to on credit at one price, regardless of the time of the month.
An additional price setting factor was that of ‘Use and Non-Use of Condoms’. Nearly a quarter of the sample indicated that they would vary their price based on whether they used protection or not.
Factors Influencing Price, (n=55)
USE AND NON USE OF CONDOMS 23.64% TIME (Taken/Month/Sex Styles) 29.09% SIZE, STYLE, TIME TAKEN 7.27% SEXUAL ACTIVITY WANTED 1.82% OWNER OF THE HOUSE PRICE 1.82% NATIONALITY OF CLIENT 5.45% FINANCIAL STATUS 21.82% ENVIRONMENT (LOCATION/REGULAR CLIENTS) 5.45% DESPERATION (Needs) 3.64%
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00%
Figure 16: Factors that Influence the Price Charged for Commercial Sex
5.2.4.7. Sexual Activities Penetrative ‘Vaginal Sex Alone’ accounted for 22.7% of the type of sexual activity disclosed. In addition, another 36.3% expressed that the sexual activities included vaginal along with some other form of sex. The ‘Anal & Oral’ alone accounted for 8.0% of the respondents. The table below however shows that there is a dynamic overlay in the types of sexual activities performed as revealed by the 75 respondents.
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Table 23: Specific Sexual Activities Performed with Clients
Specific Sex Activities Frequency Percent Cum. Percent ANAL AND ORAL 6 8.00% 8.00% MASTURBATION (Vaginal & Other Styles) 3 4.00% 12.00% NO COMMENT 1 1.33% 13.33% Oral & Other Styles (Including Anal & Vaginal) 13 17.33% 30.67%
Oral Only 4 5.33% 36.00% Other Styles (AFRICAN/DOG/COW/DONKEY) 6 8.00% 44.00% Vaginal (& other styles) 2 2.67% 46.67% Vaginal AND ANAL SEX 2 2.67% 49.33% Vaginal AND ORAL SEX 11 14.67% 64.00% Vaginal Only 17 22.67% 86.67% Vaginal SEX (& other styles with STRIPPING) 1 1.33% 88.00% Vaginal, ANAL AND ORAL 8 10.67% 98.67% Vaginal, Oral and Other Positions 1 1.33% 100.00% TOTAL 75 100.00% 100.00%
5.2.5. MSM Estimates The population of Men who have Sex with Men (MSM) was estimated using the Service Multiplier Method whereby program data from various MSM service providers was obtained i.e. total number of MSM who accessed that service during a specific period from a specific provider. The service providers visited included private medical practitioners, NGO service providers and government health facilitates. These providers were identified from the formative assessment phase, unfortunately most did not have tailored services to the specific needs of MSM.
To improve on accuracy, as many service providers as possible were located. A mini survey was then conducted during which respondents were asked whether they accessed this service during the specified time period. The respondent-driven or snowball sampling method was used whereby a ‘seed’ respondent was identified who in turn was asked to point the research team to the next person in their network. This process was repeated until the particular network was exhausted, at which point a new seed was identified and the process repeated until no new seeds are available.
5.2.5.1. MSM Mini Survey Findings A total number of 339 MSM where identified and participated directly in the MSM Mini Interview. The MSM were found in nine of the twelve districts under study. The Greater Francistown region had the bulk of the directly interviewed MSM accounting for 41.3% of the respondents.
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Table 24: Number of Men who have Sex with Men Directly Interviewed
Health Frequency Percent Cum. Percent District Boteti 10 2.95% 2.95% Chobe 9 2.65% 5.60% Greater 127 37.46% 43.07% Francistown Greater 83 24.48% 67.55% Gaborone Ngami 7 2.06% 69.62% Okavango 7 2.06% 71.68% Palapye 23 6.78% 78.47% Selebi 34 10.03% 88.50% Phikwe Serowe 26 7.67% 96.17% Tutume 13 3.83% 100.00% TOTAL 339 100.00% 100.00%
The vast majority 333 (98.2%) of the MSM identified by the snowballing are Batswana, and the remaining six were foreigners, five Zimbabwean and one South Africa. Three of the five Zimbabweans were interviewed in Serowe, one in Greater Gaborone and one was located in Francistown; while the one South African was domicile in Palapye at the time of the interviews.
Citizen Boteti Chobe Greater Greater Ngami Okavango Palapye Selebi Serowe Tutume TOTAL Francistown Gaborone Phikwe BOTSWANA 10 9 126 82 7 7 22 34 23 13 333 SOUTH 0 0 0 0 0 0 1 0 0 0 1 AFRICA ZIMBABWE 0 0 1 1 0 0 0 0 3 0 5 TOTAL 10 9 127 83 7 7 23 34 26 13 339 Table 25: Nationality of MSM Interviewed
The self-reported age distribution shows that the bulk of the respondents fall in the age range of 21 to 29 years (70.4%). This is closely aligned with the Botswana definition of youth, the distribution also resonated with informant sentiments that older men in this key population remain hidden as they are often married and very atypical members of society.
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Table 26: Age Distribution of MSM
Age Distribution of MSM Respondents (%) 12.00% 10.06% 10.00% 9.47% 8.28% 8.00% 7.40% 6.80% 6.21% 6.00% 5.33% 4.44% 4.00% 3.25% 3.55% 2.66% 2.37% 1.78% 1.78% 2.00% 0.89% 1.18% 0.30% 0.30% 0.00% 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 40 41 42 46 56 60 62
5.2.5.1.1. MSM Recent Sexual Activity Over 90% of the MSM interviewed revealed that they had either anal, oral or both forms of sexual intercourse in the last six months.
Table 27: Percentage of MSM who had Sex in Last Six Months.
Anal or Oral Sex in Last Six Months
7.96%
No Yes
92.04%
The graph below shows the number of individuals in this age distribution that admit to having had anal, oral or both types of sex. We observe that three respondents who had anal, oral or both were aged 17 years, thirty were age 22 years and eighteen were aged 29 years; as their ages increased to age 62 years only one respondent admits to having had anal or oral sex.
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Table 28: MSM having Oral or Anal Sex by Age
Anal or Oral Sex by Age
35 70 31 30 30 56 60 27 25 25 25 23 50 22 40 19 20 18 35 40 29 15 13 30 22 12 17 9
10 8 20 Age Respondents of 7 7 6 6 4 4 5 3 3 10 2 2 1 1 1 1
NumberRespondents of HadWho Anal Sex 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
No Yes Age
The sections that follow take a closer look at the service provision data in order to interogate who the service providers are that disclose delivering services to MSM. Attempts are then made to complete the service multiplier estimate where the number of key population members from the service data count and the proportion reporting having accessed the service is used to estimate MSM population.
5.2.5.1.2. MSM Access to Health Services Just under eighty percent (78.2%) of the respondents obtained health services from a programme offering MSM services.
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Table 29: Percent of MSM who Accessed Health Services
Health Service from MSM Programme, n=339
21.83%
No Yes
78.17%
The age distribution by health service or treatment seeking behavior shows that two respondents aged 17 years received services from a programme that offers MSM health services, twenty-four respondents aged 22 years, and seventeen aged 29 years obtained services from a MSM programme.
Age by Programme Service
30 28 70
24 56
25 23 60
20 19 19 19 50 20 17 40 16 35 40 14 15 29 30 22 10 9 10 17 8
6 6 20 Age Age Respondents of 4 4 4 5 3 2 2 2 10 Accessed Accessed Programme Services 1 1 1 1 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29
No Yes Age
Figure 17: Age of MSM who Accessed Programme Services
The majority of service provision was received in Francistown (34.2%) followed by Gaborone (26.5%) and Selebi Phikwe (9.7%). This corresponds with the findings that show these are the three locations where most key populations understudy reside. It is of interest that a larger number of MSM were found seeking services in Francistown than in Gaborone.
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Locations Where MSM Health Service are Obtained, n=257 40.0% 34.2% 35.0%
30.0% 26.5% 25.0%
20.0%
15.0% 9.7% 10.0% 6.2% 5.1% 4.7% 4.3% 5.0% 3.9% 1.9% 1.2% 0.8% 0.4% 0.4% 0.4% 0.4% 0.0% 0.0% 0.0%
Figure 18: Locations where MSM had Obtained Health Services in the last 6 Months
Information was gathered on the name of the establishment offering services to MSM. Civil society was the most often stated service providers while a few government and private practitioners also stated that they have MSM as clients. Table 30 shows that 75 respondents ‘did not access’ services from a provider that targets MSM; this makes the ‘valid n’ for this variable 257 (332 less 75).
Table 30: Providers from Whom MSM Received Services
From Whom Service was Received Frequency Percent Cum. Percent
Area W Clinic 2 0.60% 0.60% BOFWA 58 17.47% 18.07% BOFWA: LEGABIBO 6 1.81% 19.88% BONELA 14 4.22% 24.10% Borolong Clinic 1 0.30% 24.40% Chadibe Clinic 1 0.30% 24.70% Don't Remember 1 0.30% 25.00% Gerald Estates Clinic 1 0.30% 25.30% Kasane Health Post 1 0.30% 25.60% LEGABIBO 53 15.96% 41.57% MEN FOR HEALTH 49 14.76% 56.33% Did Not Access 75 22.59% 78.92% PHASE 2 CLINIC 1 0.30% 79.22%
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From Whom Service was Received Frequency Percent Cum. Percent
PMCFMH 12 3.61% 82.83% Sedie Clinic 2 0.60% 83.43% Silence Kills 18 5.42% 88.86% TEBELOPELE 32 9.64% 98.49% TEBELOPELE: LEGABIBO 5 1.51% 100.00% TOTAL 332 100.00% 100.00%
Figure 19 shows that BOFWA (58), LEGABIBO (53), Men for Health (49), Tebelopele (32) and Silence Kills (18) are leading service providers to MSM. The data in table 30 shows that nearly a quarter (22.59%) of the respondents did not access services over the past six months, from a programme targeting MSM. This means that the 75 individuals answering this question either did not need or were unable to obtain services from a ‘MSM programme that specifically targets MSM”. They may have foregone the services, not needed services or gone to a non MSM specific health care provider.
MSM Service Provider Access, n=257
BOFWA 58 LEGABIBO 53 MEN FOR HEALTH 49 TEBELOPELE 32 Silence Kills 18 BONELA 14 PMCFMH 12 BOFWA: LEGABIBO 6 TEBELOPELE: LEGABIBO 5 Sedie Clinic 2 Area W Clinic 2 PHASE 2 CLINIC 1 Kasane Health Post 1 Gerald Estates Clinic 1 Don't Remember 1 0 10 20 30 40 50 60 70
Figure 19: Frequency Distribution of Services Provider
MSM specific service provision was found in nine of the twelve health districts shown in figure 20. Only 322 respondents answered the question, “Over the past six months, did you receive service from a program targeting MSM?” Figure 19 above shows that 75 respondents did not access MSM specific Services. The remaining respondents who said they had received services from a program targeting MSM were asked to name the provider. LEGABIBO was found as the only service provider in Boteti
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District (10) while Kasane Health Post (1), LEGABIBO (1) and Tebelopele (4) are three service providers in Chobe offering services to MSM, details are shown in figure 20.
The largest number of MSM (96 in total) were found to be receiving services in Greater Francistown. The service providers in Francistown are; the Government Area W Clinic (2), BOFWA (47), BOFWA: LEGABIBO (3), BONELA (4), Borolong, Gerald Estate and Chadibe
Clinic (each serviced 1 MSM), LEGABIBO (28), Men for Health (1), Tebelopele (6) and Tebelopele: LEGABIBO (5). The next largest number serviced was in Gaborone, a total of 66 MSM receiving services from Men for Health (44), LEGABIBO (9), BOFWA (5), BOFWA: LEGABIBO (3), PMCFMH (3) and BONELA (2).
MSM Service Provider by Health District, n=257
BOFWA 47 5 LEGABIBO 28 9 MEN FOR HEALTH 1 44 TEBELOPELE 6 Silence Kills BONELA 1 2 PMCFMH 3 BOFWA: LEGABIBO 3 3 TEBELOPELE: LEGABIBO 5 Sedie Clinic Area W Clinic PHASE 2 CLINIC Kasane Health Post Gerald Estates Clinic 1 Don't Remember Chadibe Clinic 1 Borolong Clinic 1 0 10 20 30 40 50 60 70
Boteti Chobe Greater Francistown Greater Gaborone Kgalagadi North Kweneng West
Ngami Okavango Palapye Selibe Phikwe Serowe Tutume
Figure 20: Service Provider where MSMs Receive Services by District
5.2.5.1.3. Service Provider Data Seven of the facilities offering services to MSM are government facilities; key staff were interviewed in an attempt to understand how data relating to MSM are collected and maintained. These facilities across all the districts disclosed that they do not maintain formal records for key populations and that they offer services to all regardless of sexual orientation. This finding means that even though MSM access services from government, no (n) value can be determined for government facilities as required in the service multiplier method formula, where N= n/p because the present record keeping system does not capture specific key populations.
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Similarly, private practitioners were not able to provide a registered list or record number for the number of MSM patients. Civil society organisations are hence the only entities with number available for the MSM they offer services to.
5.2.5.1.4. Service Multiplier Calculation The Civil Society entities by location and the number of MSM that were interviewed are shown in the matrix below (table 31). LEGABIBO was named as the provider by MSM respondents in Dukwi (1), Francistown (24), Gaborone (9), Jwaneng (1), Letlhakane (10), Maun (3), Sebina (2), and Borolong (2) where they had received targeted programme services. Similarly, Tebelopele was named in Francistown (6), Kasane (4), Maun (1), Palapye (6) and Serowe (15) by the mini-survey participants. The table presents a full distribution of the civil society service providers named by MSM during the survey as well as the government, private column for facilities that do not maintain MSM client records.
Table 31: Service Providers Named by MSM as a Source of Service for their Needs
Location Service GoB & BOFWA BOFWA: BONELA LEGABIBO MEN FOR PMCFMH Silence TEBELOPELE TEBELOPELE: TOTAL Received Private LEGABIBO HEALTH Kills LEGABIBO
BOROLONG 1 0 0 0 2 0 0 0 0 0 3 CHADIBE 1 0 0 0 0 0 0 0 0 0 1 DUKWI 0 0 0 1 0 0 0 0 0 1 FRANCISTOW 3 47 3 0 24 0 0 0 6 5 88 N GABORONE 1 5 3 2 9 45 3 0 0 0 68 JWANENG 0 0 0 1 0 0 0 0 0 1 KASANE 0 0 0 0 0 0 0 4 0 5 LETLHAKANE 0 0 0 10 0 0 0 0 0 10 MAUN 2 6 0 0 3 0 0 0 1 0 12 NATA 0 0 1 0 0 0 0 0 0 1 NKANGE 0 0 0 0 0 0 0 0 0 0 PALAPYE 0 0 0 0 4 2 1 6 0 13 SEBINA 0 0 0 2 0 0 0 0 0 2 SELIBE 1 0 0 0 0 0 7 17 0 0 25 PHIKWE SEROWE 1 0 0 0 0 0 0 0 15 0 16 TONOTA 0 0 0 0 0 0 0 0 0 0 TUTUME 0 0 11 0 0 0 0 0 0 11 TOTAL 10 58 6 14 52 49 12 18 32 5 257
Using the health district data together with the MSM service provider data we are now able to use the Service Multiplier Method to estimate the total number of MSM in nine (9) of the districts as these have data available as required by the formula. The three remaining districts either did not reap ‘seeds’ for the snowballing technique or did not have service register data for MSM.
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Table 31 provides a total pool of 257 MSM who received health services. Of this number nine (9) were public sector providers who do not maintain MSM records and can therefore not be included in the calculation. An additional MSM (1 individual) in Serowe reported receiving targeted health services but could not recall the service provider name and as such is also not eligible to be part of the service multiplier calculation. A total of 10, Government, Private, and do not remember are hence removed from the initial 257 that report receiving serving leaving 247 MSM as the valid number to include in the service multiplier estimate calculation.
Table 32 shows that all 10 respondents that were directly interviewed in the Boteti District revealed receiving health services from a provider that targets MSM. The proportion of those who said yes, to those in the sample directly interviewed is therefore 1. In the Chobe district this number is 5 out of 9 while in Greater Francistown it is 91 out of 127. This proportion or ration is presented in the table as ‘p’.
The table also provides district level data for all the service providers, who provide targeted services to MSM in the district. This data was obtained independently from the registers of the service providers for the same time frame as that of the mini-survey interviews. This is denoted by the variable ‘r’ in the table where the service provider in Boteti had 225 MSM in its register. In Chobe the providers had 10 while in the providers had 289 MSM in their registers. The unique case of Kgalagadi north where no MSM was interviewed but the service provider register had 20 individuals was therefore taken as the de facto number for MSM in that district. The final estimate being 2,625 MSM across 10 of the surveyed districts.
Table 32: Total Estimate of MSM across the surveyed districts
West
North
Selebi
Boteti
Chobe
Ngami
TOTAL
Phikwe
Serowe
Greater Greater Greater Tutume
Service Provider Palapye
Kweneng Kweneng
Kgalagadi Kgalagadi
Gaborone
Okavango Francistown
BOFWA 0 0 47 5 2 4 0 0 0 0 58
BOFWA: LEGABIBO 0 0 3 3 0 0 0 0 0 0 6
BONELA 0 0 1 2 0 0 0 0 0 11 14
Don't Remember 0 0 0 0 0 0 0 0 0 0 0
LEGABIBO 10 1 28 9 3 0 0 0 0 2 53
MEN FOR HEALTH 0 0 1 44 0 0 4 0 0 0 49
PMCFMH 0 0 0 3 0 0 2 7 0 0 12
Silence Kills 0 0 0 0 0 0 0 18 0 0 18
TEBELOPELE 0 4 6 0 0 1 6 0 15 0 32
TEBELOPELE: LEGABIBO 0 0 5 0 0 0 0 0 0 0 5
TOTAL (From Whom Received) 10 5 91 66 5 5 12 25 15 13 247
Total MSM Interviewed (n) 10 9 127 83 7 7 23 34 26 13 339
Proportion who said they received service, (p) 1.000 0.556 0.717 0.795 0.714 0.714 0.522 0.735 0.577 1.00 0.729
Register (r ) 225 10 289 362 20 192 234 107 267 178 1884
Estimated MSM Pop - (N) = r/p 225 18 403 455 20 269 449 146 463 178 2625
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5.2.5.1.5. MSM Service Satisfaction All respondents were asked whether they were satisfied with the service they received from the providers, this included service received from the government facilities which expressed that they do not make exception for individuals based on their sexual preferences. The data shows that almost all the MSM interviewed were happy with the services they received. The reasons forwarded for dissatisfaction were; “The nurse is not informed about MSM, needs more education”, “Lack of knowledge on MSM issues”, and “Poor time management”.
Table 33: MSM Reason for Level of Satisfaction with Services Received
Why NOT satisfied Frequency Percent Cum. Percent Lack of knowledge on MSM issues 1 0.29% 0.29% Satisfied with the Service (N/A) 336 99.12% 99.41% Poor time management 1 0.29% 99.71% The nurse is not informed about MSM, need 1 0.29% 100.00% more education TOTAL 339 100.00% 100.00%
HIV testing & counselling stood (70.0%) out as a major service that MSM received from the service providers. Condoms and Lubricants were a distance 8.17% from the HIV testing that clients receive while only one MSM mentioned ‘Anusol Cream’ as a product received during service.
Table 34: Name of the Type of Service Received
What was the Service Received Frequency Percent Cum. Percent Condoms and or Lubricants (& related services) 21 8.17% 8.17%
Counselling & or Psycho Social Support 5 1.95% 10.12% EDUCATION (HIV and or STI's &/ Human Rights) 5 1.95% 12.06%
GROUP DISCUSSION 9 3.50% 15.56% HIV TESTING (& or Counselling) 180 70.04% 85.60% HIV TESTING AND DISTRIBUTION OF CONDOMS 9 3.50% 89.11% (AND or LUBRICANTS) HIV TESTING AND STI SCREENING 19 7.39% 96.50% HIV TESTING, SOCIAL SUPPORT 1 0.39% 96.89% HIV TESTING, STI SCREENING, CANCER 1 0.39% 97.28% SCREENING HTC AND ARV Services 5 1.95% 99.22% MINIMAL SERVICE PACKAGE 1 0.39% 99.61% SIPOSITORIES (ANUSOL) AND CREAM 1 0.39% 100.00% TOTAL 257 100.00% 100.00%
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Respondents were asked what the particular type of services they received from service providers. The vast majority (69.6%) named HIV Testing and or Counselling as the service the used. Condoms & lubricants (8.4%) and Screening for STIs (8.0%) are also on the top of the service requirements of MSM.
Array of Services Received by MSM
HIV TESTING (& or Counse 69.6% Condoms and or Lubricant 8.4% HIV TESTING AND STI SCRE 8.0% GROUP DISCUSSION 3.2% HIV TESTING AND DISTRIBU 1.2% ENROLMENT 1.2% Counselling 1.2% SAFER SEX Commodities & 0.8% PSYCHO-SOCIAL SUPPORT 0.8% HTC AND ARV Services 0.8% HIV TESTING AND PROVISIO 0.8% EDUCATION (HIV and or ST 0.8% SIPOSITORIES (ANUSOL) AN 0.4% MOONLIGHT TESTING, CONDO 0.4% MINIMAL SERVICE PACKAGE 0.4% HUMAN RIGHTS EDUCATION 0.4% HIV TESTING, SOCIAL SUPP 0.4% HIV TESTING AND PROVISIO 0.4% HIV TESTING AND HOW TO U 0.4% HIV TESTING AND DISTRIBU 0.4% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
Figure 21: Array of Services Received by MSM
A closer look at the providers offering HIV Testing and or Counselling to the MSM interviewed is shown in the bar chart below. BOFWA, LEGABIBO and Tebelopele are seen in the higher end of the scale as the named providers.
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HIV TESTING (& or Counselling)
TEBELOPELE: LEGABIBO TEBELOPELE Silence Kills Sedie Clinic PMCFMH PHASE 2 CLINIC N/A MEN FOR HEALTH LEGABIBO Kasane Health Post Gerald Estates Clinic Don't Remember Chadibe Clinic Borolong Clinic BONELA BOFWA: LEGABIBO BOFWA Area W Clinic ABO 0 5 10 15 20 25 30 35 40 45 50
Figure 22: Service Providers offering MSM HIV Testing and Counselling
5.2.6. Transgender Estimates Transgendered individuals were not part of the 2012 study, this is therefore the maiden study of its kind in Botswana to attempt to obtain a size estimate of transgendered individuals. Focus group meetings and Key Informant Interviews were under taken as narrated above in the mapping section of this report. Size numeration then took place at a different time after the completion of the mapping.
The formative discussions at both the mapping level and during the size estimation confirmed the high levels of stigma that were hypothesis in the study protocol towards people with alternative sexual orientation to that or the society at large. This was confirmed through subtle practices such as giving medical cards to transgender people that do not match their chosen sex. Trans-women are often given blue medical cards which are to be given to males while Trans-men are given pink medical cards which are to be given to females. Several other discriminatory activities were pointed out that relate to social issues, personal issue, issues with families, and religious issues. These will be elaborated further in the discussion section of this report.
5.2.6.1. TG Mini Survey Findings A total of 47 transgendered individuals were located and interviewed through direct one on one (individual) interviews. The overwhelming majority were comfortable in disclosing that they had had sex in the last six months.
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Table 35: Transgender Sex in Past Six Months
Sex Past Six Frequency Percent Cum. Months Percent Yes 45 95.74% 95.74% No 2 4.26% 100.00% TOTAL 47 100.00% 100.00%
All the respondents disclosed their age. The respondents were aged 20 to 34 years. The majority being aged 26 and below as shown in the graph.
Age of the Respondents, n=47 25.00%
20.00%
15.00%
10.00%
5.00%
0.00% 20 21 22 23 24 25 26 27 28 31 34
Figure 23: Age Distribution of Transgender Respondents
The 47 respondents were interviewed in five of health districts. It proved difficult to find and hold meetings in all of the districts because of how the law and society as a whole relates to transgendered people. The findings show that the majority of transgendered people were found in Gaborone (80.9%). Palapye and Francistown then each accounted for 6.4% of the TGs interviewed. The table that follows shows the data for all the five districts.
Table 36: Transgender by District
GF District Name Frequency Percent Cum. Percent Chobe 2 4.26% 4.26% Greater Francistown 3 6.38% 10.64% Greater Gaborone 38 80.85% 91.49% Kweneng West 1 2.13% 93.62% Palapye 3 6.38% 100.00% TOTAL 47 100.00% 100.00%
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Respondents were asked if they had received TG services in the last six months. Under sixty percent (57.5%) said yes, they had received TG specific services. The table below shows the distribution of respondents who received services.
Table 37: Transgender Service Received in Last 6 Months
ServiceTGLast6months Frequency Percent Cum. Percent Yes 27 57.45% 57.45% No 20 42.55% 100.00% TOTAL 47 100.00% 100.00%
The services received from the providers by the TGs interviewed are shown in the chart below. Fifteen of the 27 respondents who received services disclosed what the types of services are that they received in the last six months. Counselling is the service most (27%) receive. A number of the TGs interviewed expressed the challenges they face living within and being accepted by people in the society at large. A good number also express the deeper challenge of not being accepted by their own families presenting psychological pressure on the individuals. Knowledge and information on transgender issues collectively accounts for 20% of the services received followed by health care (13%), lube & condoms (13%), and the attendance of workshops on removing legal barriers (13%).
Type of Services TG Received
COUNSELLING 26.67%
REMOVING LEGAL BARRIERS WORKSHOP 13.33%
LUBE & CONDOMS 13.33%
KNOWLEDGE ON TRANSGENDER ISSUES 13.33%
HEALTH CARE 13.33%
MEDICAL SERVICES 6.67%
INFORMATION ABOUT TRANSGENDER… 6.67%
COUNSELLING & MEDICAL SERVICES 6.67%
0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%
Figure 24: Type of Services Received by Transgender Respondents
The survey explored whether the respondents who received services were happy with the services they received. The level of satisfaction recorded 93.1% saying that they were satisfied with the services they received.
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The data also shows that of the 45 respondents who reported having sex in the last 6 months only 26 (57.8%) are receiving TG specific health services.
Table 38: Transgender Sex in Last Six Months
Sex Past Six Months Service TG Last 6 months Yes No Total Yes 26 1 27 Row % 96.30% 3.70% 100.00% Col % 57.78% 50.00% 57.45% No 19 1 20 Row % 95.00% 5.00% 100.00% Col % 42.22% 50.00% 42.55% Total 45 2 47 Row % 95.74% 4.26% 100.00% Col % 100.00% 100.00% 100.00%
Six service provider categories were named by twenty-two TGs who received services as places where they received TG specific health services.
Table 39: Transgender Service Providers
Provider Name (If Yes) Frequency Percent Cum. Percent BOFWA 1 4.55% 4.55% HEALTH EMPOWERMENT 1 4.55% 9.09% RIGHTS LEGABIBO 8 36.36% 45.45% PRIVATE DOCTOR 1 4.55% 50.00% RAINBOW IDENTITY 10 45.45% 95.45% TEBELOPELE 1 4.55% 100.00% TOTAL 22 100.00% 100.00%
No government facility was found to offer TG specific services and only one private doctor was named as a TG specific service provider. All the other TG respondents receive their services through civil society groups that are based either in Gaborone or Francistown.
Table 40: Location of TG Service Providers
City/Town Service Received BOFWA HEALTH LEGABIBO PRIVATE RAINBOW TEBELOPELE TOTAL (If Yes) EMPOWERMENT DOCTOR IDENTITY RIGHT FRANCISTOWN 1 0 1 0 0 1 3 GABORONE 0 1 7 1 10 0 19 TOTAL 1 1 8 1 10 1 22
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5.2.7. PWIDs Estimates The Botswana Substance Abuse Network was a major source of information with regard to people who inject drugs. MSM were also used as a linkage to identify PWIDs.
5.2.7.1. Awareness of PWIDs The survey did not directly identify any individuals who identified as PWIDs, the study protocol however determined from the outset that members of the other KP groups may be a good source that could provide information or linkages to people who inject drugs for none medical reasons. Almost 16% of all the MSM interviewed said they know of at least one person who injects drugs. This infers that there are at least 54 individuals believed to be using drugs through injectable methods. The respondents were however not able to definitively direct the research team to any of the PWIDs to have a direct interview with them.
Table 41: Knowledge of PWIDs
Know PWIDs Frequency Percent Cum. Percent No 285 84.07% 84.07% Yes 54 15.93% 100.00% TOTAL 339 100.00% 100.00%
Those who say they know PWIDs are largely in the 20 to 30 year age group.
Age Distribution of Those who know PWIDs 8
7
6
5
4
3
2
1
0 0 10 20 30 40 50 60 70
Figure 25: Age Distribution of Those who Know PWIDs
The majority of those who say they know people who inject drugs are in Greater Francistown (79.6%) followed by Greater Gaborone (18.5%).
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Table 42: Knowledge of PWIDs by District
Name of GF District * Know PWIDs Name of GF District No Yes TOTAL Boteti 10 0 10 Chobe 8 1 9 Greater Francistown 97 43 140 Greater Gaborone 73 10 83 Ngami 7 0 7 Okavango 7 0 7 Palapye 23 0 23 Selebi Phikwe 34 0 34 Serowe 26 0 26 TOTAL 285 54 339
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6. Discussion This Mapping & Size Estimation survey identified a total of 280 FSW hotspots country wide. There were several similarities between the Addis Abba study and the current Botswana Mapping and Size Estimation Survey. Addis Abba data was drawn upon from a time when the city had a population of 2 million; there were 16 streets/localities where street-based sex workers worked regularly. On three different visits between 2200 and 0200 hours, the average total number of street-based sex workers observed at the 16 localities was 258, reporting on average two sex clients per day. Observations made by the field supervisors and coordinators in each locality (Fridays, Saturdays and Sundays) indicated that the numbers of street-based sex workers were low compared with previous estimates. Observations for the mapping and census of street-based sex workers were made from Friday to Sunday, as these were perceived to be peak hours for the street based sex workers in much the same way as the Botswana survey.
6.1. FSW Estimates A total of 280 hotspots were enumerated across the 12 districts. The hotspots identified in each of the health districts show that the highest number of hotspots were identified in the Greater Gaborone area followed by Francistown. Independent data from Statistics Botswana shows the current selection of registered commercial and retail outlets country wide are at 504. In addition to the Statistics Botswana data, two local town councils (Selebi-Phikwe and Ngamiland) provided their own independent data for licensed operating venues in their business centres. This data provides an additional triangulation point for the hotspot verification against what the survey mapped. The data in Ngamiland in particular confirms the larger number of outlets are indeed present and that the direct mapping fell significantly short in identifying them in this district.
Selected Commercial Retail Business Outlets, n=504
Investment Enterprise 168 Bar 92 Lodge 83 Bottle Store 33 Hotel 32 Camp 26 Safaris 18 Liquor Restaurant 17 Guest House 15 Administrative Head 9 Pub/Tavern 2 Motel 2 General Dealer 2 Co-op 2 Mess 1 Club 1 Butchery 1 0 20 40 60 80 100 120 140 160 180
Figure 26: Statistics Botswana Commercial Retail Outlets
Source: Statistics Botswana, 2017
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The data in the graph above attempts to mirror the mapping and size estimation ‘hotspots’ as closely as possible to conform to the definition used in the survey. Butcheries are included as they are retail outlets which in some cases act as an actual meeting place where meat is roasted and alcohol sold in close proximity. The top end of the graph shows ‘Investment Enterprises’. This is a broad category from which we do not want to lose any potential outlet types that may conform to the ‘hotspot’ definition. The varied economic activity in all the selected data sets are shown in the table below.
Table 43: Economic Activity by Outlet Type
Outlet Type * ECONOMIC ACTIVITY (n=504) Outlet Type Accommodation Accommodation Food, Food, Manufacture of Manufacture TOTAL (Camps, Parks) (Lodges, Camps, Beverage & Beverage & Malt Liquor of Soft Hotels) Tobacco Tobacco Drinks Administrative 1 0 0 0 7 1 9 Head Bar 0 1 0 91 0 0 92 Bottle Store 0 0 0 33 0 0 33 Butchery 0 0 0 1 0 0 1 Camp 5 21 0 0 0 0 26 Club 0 0 0 1 0 0 1 Co-op 0 0 0 2 0 0 2 General Dealer 0 0 0 2 0 0 2 Guest House 1 14 0 0 0 0 15 Hotel 0 32 0 0 0 0 32 Investment 5 107 0 56 0 0 168 Enterprise Liquor Restaurant 0 2 5 10 0 0 17 Lodge 0 83 0 0 0 0 83 Mess 0 0 0 1 0 0 1 Motel 0 2 0 0 0 0 2 Pub/Tavern 1 0 0 1 0 0 2 Safaris 9 9 0 0 0 0 18 Source: Statistics Botswana, 2017
The survey identified 280 outlets in comparison to the 504 outlets contained in the Statistics Botswana data. The Statistics Botswana data is however nation-wide while the mapping survey was conducted in 12 GF Districts. When isolated by Global Fund District the Statistics Botswana data contains 381 ‘hotspot’ outlets that conform to the survey definition, this show that there are about 100 more outlets in the 12 districts than the study directly mapped.
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Estimated FSW Distribution by District
4 Tutume 4 7 Serowe 14 26 Selebi-Phikwe 22 47 5 Palapye 15 8 Okavango 8 8 Ngami 89 119 8 Kweneng West 9 8 Kgalagadi North 9 122 Greater Gaborone 134 61 Greater Francistown 39 15 Chobe 26 8 Boteti 12 0 20 40 60 80 100 120 140 160
Mapped Numerated Outlets Licensed Venues Local Town Councils Registered Comercial Outlets (SB)
Figure 27: Licensed Commercial Outlets versus Directly Mapped Venues
The Census Size Estimation allows for network scale up adjustment where the number of directly observed key population at a given outlet or location is adjusted by the ratio of documented outlets over the number observed; where the documented number exceeds the numerated, and for the numbers to remain the same where the numerated exceed the documented. This allows for the hidden nature of the populations under survey to be adjusted for.
Table 44 provides the three sets of data, that is, Statistics Botswana, Local Town Council and the current survey data. The venue shortfall column shows the difference between the survey mapped data and the largest documented licensing data. In the case of both Ngamiland and Selebi-Phikwe the local council data which is closer to this actual source was selected as the preferred venue count. The resultant estimate of FSWs across the 12 health district is therefore determined to be 6718.
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Table 44: Network Scale up Factor Calculation
Registered Licensed MSE Venue NSU FSW Adjusted Commercial Venues Local Numerated (Hotspot) Factor Directly FSW Outlets (SB) Town Councils Venues Shortfall Observed Estimate Boteti 12 8 4 1.5000 23 35 Chobe 26 15 11 1.7333 394 683 Greater 39 61 -22 1.0000 687 687 Francistown Greater 134 122 12 1.0984 1494 1641 Gaborone Kgalagadi 9 8 1 1.1250 55 62 North Kweneng 9 8 1 1.1250 26 29 West Ngamiland 89 119 8 111 14.8750 181 2692 Okavango 8 8 0 1.0000 50 50 Palapye 15 5 10 3.0000 76 228 Selebi-Phikwe 22 47 26 21 1.8077 287 519 Serowe 14 7 7 2.0000 45 90 Tutume 4 4 0 1.0000 2 2 Total 3320 6718
The ratio of Female Sex Worker to the total female population has been estimated in several studies to range from 1 percent to 18 percent. There are often outlying factors and circumstances leading to extreme outliers as every country circumstance is different. The total bar-based sex worker population in a Bulawayo based study was estimated at ~9500, this included women who did not solicit in bars, the total sex worker population in Bulawayo was estimated at almost 12,00017. A similar capture recapture study in Mutare, estimated that between 1600 and 2000 women were selling sex over the two weekends of the study.
Data from Tete province in Mozambique which lies on a major trucking route from Zimbabwe and where a third of the population attending the clinic were Zimbabwean shows that sex worker to the general female population ranges from as low as 2.5% sex workers per female population to as high as 18% depending on the method of enumeration used.
Prevalence of FSW according to the NSU (Network Scale-up Method) is 1.03% in Tbilisi and 2.42% in Batumi. Comparisons of Georgia estimates (from the NSU method) with the regional estimates indicate Georgia FSW prevalence is within the range of regional recommendations of UNAIDS. The table that follows shows the district and national average for the 12 health districts using the ‘Adjusted Female Sex Worker Estimate’ [n=6718].
17 Ngugi EN, Wilson D, Sebstad J, Plummer FA, Moses S. Focused peer-mediated educational programs among female sex workers to reduce sexually transmitted disease and human immunodeficiency virus transmission in Kenya and Zimbabwe. Journal of Infectious Diseases. 1996;174:S240-S7.
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Table 45: Ratio of Female Sex Worker to Total Female Population
Adjusted FSW: Female GF District Total Male Female FSW Total Popn Estimate Boteti 57,376 28,142 29,234 35 0.120% Chobe 23,347 12,023 11,324 683 6.031% Greater Francistown 159,225 76,712 82,513 687 0.833% Greater Gaborone 573,358 279,466 293,892 1,641 0.558% Kgalagadi North 20,476 10,352 10,124 62 0.612% Kweneng West 47,797 24,407 23,390 29 0.124% Ngamiland (East & West) 149,755 72,316 77,439 2,692 3.476% Okavango (Ngamiland Delta) 2,529 1,277 1,252 50 3.994% Palapye 41,102 21,476 19,626 228 1.162% Selebi Phikwe 49,411 24,749 24,662 519 2.104% Serowe 57,588 27,749 29,839 90 0.302% Tutume 147,377 70,330 77,047 2 0.003% 12 District National Average FSW to Total Female Popn: 1.61%
The FSW to Female Population estimate is 1.61% showing a very close alignment to the range found in Ethiopia where a total of 258 street-based sex workers were identified in Addis Ababa. Among this group, most respondents stated that the number of street-based sex workers had decreased in comparison with previous years for the following reasons: sex clients had transferred their attentions to other population groups, such as high school or night school students, home girls and office girls; some sex workers had left Ethiopia and moved to jobs in Middle Eastern countries; and some had left Addis Ababa to work as sex workers in other regional towns. These findings suggest a close relationship between the national income status of the country and the prevalence of commercial sex work. Notwithstanding, this Botswana ratio of 1.61% is not too far from the Mutare, 1993 comparative study previously referred to herein.
6.2. MSM Estimates A total number of 339 MSM where identified and participated directly in the MSM Mini Interview. The MSM were found in nine of the twelve districts under study. The adjusted total based on the service multiplier is 26650.
Attempts were made in all 12 districts to locate and interview as many service providers as possible and obtain programme data from these providers; specifically, the total number of MSM who accessed service during a specific period from a specific provider. The service providers visited included private medical practitioners, NGO service providers and government health facilitates. These providers were identified from the formative assessment phase, unfortunately most did not have tailored services to the specific needs of MSM and MSM data was unreliable.
The majority of service provision was received in Francistown (34.2%) followed by Gaborone (26.5%) and Selebi Phikwe (9.7%). While this corresponds with the findings that show these are the three
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 82 locations mostly occupied by the key populations understudy it is interesting to see that the proportion of MSM in Francistown exceeds those in Gaborone.
6.3. TG’s Estimates A total of 47 transgendered individuals were located and interviewed through direct one on one (individual) interviews. Two thirds of the TG respondents had received TG specific services of which counselling was top of the list. One third were hence not obtaining services, they disclose that medical assistance was not tailored to their specific needs because of the attitude of health providers; they are often given medical cards which do not match their sex, Trans women are often given blue medical cards which are to be given to male while Trans men are given pink medical cards which are to be given to females. In addition to the health personnel there are social, family and legal issues that offend TGs on a daily basis, these include-
Social Issues Transgender people are usually harassed for not behaving or conducting themselves according to their birth sex. TGs are unable to use public toilets because people don’t understand their sexuality, if they do use public conveniences the conditions are uncomfortable. They face threats of which sometimes is life threatening; they are threatened or physical assaulted. Society often view TGs as having hormonal imbalance.
Personal and Family On the personal level TGs are often depressed as they are seen as an abomination, often loosing friends and in some cases outcast by their families. These pressures are said to being a cause of suicidal thoughts. They are forced to wear clothes they don’t want to wear or they are not comfortable in. Parents threaten to stop paying for their school fees because they do not condone their trans-behavior. They sometimes get punished or beaten by family members/parents for trans-behavior. The list of personal infringements from the TG perspective is endless, religion, social practices, poverty and unemployment all have an impact on how TGs integrate or rather fail to integrate and remain as a hidden population.
6.4. PWIDs Estimates The survey was unable to estimate a number of PWIDs. The study protocol identified MSM as the link to PWIDs. MSM mentioned knowledge of 54 individuals who were believed to be using drugs through injectable methods. The respondents were however not able to definitively direct the research team to any of the PWIDs to have a direct interview with them. The survey hence reports the actual number of PWIDs as zero.
6.4.1. BOSASNET The Botswana Substance Abuse Support Network (BOSASNET) served as an additional informant to provide leads to a deeper understanding of the severity of drug abuse in the country with a specific focus on the use of injectables. This is the only network in Botswana with a national mandate to address issues of substance abuse and manage its consequences. The network has been in existence since 2008 with the purpose of providing education to prevent substance abuse and rehabilitation to people who are already abusing habit forming substance of any kind.
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The network recognized the problem of substance abuse in Botswana as wide spread, but thankfully observe that the use is seldom through injecting drug use. They are in a very good position to observe clients who may be injecting drugs as they have regular and frequent clients. The networks estimate is that in a cohort of two to 300 hundred drug users there would probably be one who uses through injecting. Injecting users at BOSASNET are identified through telltale marks on certain parts of their bodies, but they are few and far between.
According to the network there are several reasons why injecting is a big no in Botswana and hopefully will remain that way for some time. Culture plays a big part in this, for one to be injected people believe that you have to be extremely ill, and as a result one on wants to voluntarily perform the act of injecting. Another reason is around accessibility. Obtaining needles as a non-medical person is very hard, one would struggle to explain why they need a needle when you can go to a health facility at almost no cost for any medical treatment that needs to be injected. As a result, the observation is that medical staff themselves are the most likely ones to fall into the PWIDs category, and experience in the network has actually confirmed this. The cost of needles and drugs are another inhibiting factor to the practice of injecting. People weigh the cost of an injectable high against that of other means of achieving intoxication and usually find non-injecting methods more affordable and more accessible.
Injecting drugs use, according to BOSASNET is hence privilege of the affluent in society, a sentiment that was echoed by key informants in the formative assessment component of the survey. BOSASNET hence held the opinion that it would be extremely difficult to locate PWIDs in Botswana at this stage and it would be highly inappropriate for them to suggest any individual as a lead or seed to approach for further information or self-disclosure as a KP of this group for the purposes of size estimation.
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7. Conclusion and Recommendations The objectives of this survey was to establish geographic hotspots where key populations are found in the selected 12 districts across Botswana, establish the size of the four populations and strengthen the capacity of local institutions to conduct mapping and size estimation of key populations. The survey information is intended to help the national response to HIV and AIDS, so as to plan and target KPs in a resource wise manner.
7.1. Geographical Mapping The survey provides detail geographical maps of 280 hotspots across the 12 districts showing the presence of FSWs. The mapping also shows whether MSM, TGs or PWIDs were found or patronize the said locations. A determination was made at the project design stage that ‘hotspot venues’ were used as a point of reference only for FSW; other methods were used to map MSM, TGs and PWIDs. These methods however still provided sufficient data at the town and village level to determine the presence of the latter three KPs but are not directly linked to hotspots.
7.2. Separating Mapping & Size Estimation The survey undertook district sensitization, mapping and size estimation as separate components at different timeframes. Separating these functions significantly increases the resource requirements of the exercise highlighting the need for careful consideration at the planning phase as to whether this is the preferred route. The lay of the land in a sparely populated country like Botswana further exacerbates the resource needs due to the long distances that must be covered in order to locate survey participants.
Separating the mapping function and the size estimation has numerous advantages. Undertaking the mapping first provides valuable district level information regarding a wide variety of social factors affecting key populations. With the mapping done first, the information about movement, presence and any recent behavioral trends can be carefully analyzed before embarking on the size estimation. It is hence recommended that a good cost-effect balance would be to combine the community stake holder sensitization visits with the mapping component of the survey; and then separately conduct the size estimation.
7.3. Peer Outreach Worker Training The formative assessment, and the involvement of civil society groups and peer outreach workers is a vital part of the mapping and size estimation survey. Civil society groups were the only service providers found to maintain key population specific service data. Civil society groups are also the gateway to locating and convincing key populations to participate in a survey of this nature. It is hence recommended that the civil society groups should be part of all training sessions. Trainings are a key part of the design phase, where field supervisors are appraised of the study details; trainings must hence be structured in a careful way to have sessions that include civil society groups that work with key populations as well as the peer outreach worker sessions. It is however noted that it is more resource effective to run peer outreach trainings at the district level.
7.4. Qualitative Data The value of qualitative information in mapping and size estimation cannot be overstated. At face value estimating the size of key populations appears to be a numbers game, but without a clear understanding
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 85 of the qualitative issues that key populations face and the drivers of their decision making processes size estimation will be left wanting. It is hence recommended that adequate time be allotted to all stakeholder and key informant data collection at the mapping stage. Strides should be taken to have an individualized mapping report as a stand-alone document from the size estimation report.
7.5. Size estimation This survey concludes the size estimate of FSWs across the 12 health district is 6718. It is recognized that every survey of this nature will only present an ‘estimate’ as there are numerous exogenous factors that affect these estimates from the chosen methodology to the behavior of the KPs themselves. The tourism sector for example, in this study is seen to have a sizable impact in the estimates of FSWs. This should not come as a surprise, but should rather inform policy and planning which focuses on the unique nature of the said geographic areas.
The absence of people who inject drugs in two consecutive studies of this nature over five years presents a conclusion that their number is truly so insignificant that any programme targeting PWIDs in Botswana at this time will be an ineffective use of resources. PWIDs as a target audience should hence be downscaled giving priority focus to those KP groups that are prominent and face a higher risk of incidence and prevalence of HIV. PWIDs do not have to be totally omitted from the national agenda but instead new methodologies may be investigated for tracing this group, this should include rethinking the use of MSM alone as the KP group that is well positioned to link research to PWIDs. Consideration should be given to a stand-alone PWIDs formative assessment.
The size estimate for MSM is concluded at 2675. The service multiplier method used to determine this number is based on ten health districts; that is the MSM for two districts are recorded as zero in order to apply the method consistently across all districts. The three districts, Gaborone, Francistown and Kasane which were numerated in 2012 at 700 MSM show a marked difference in this survey as they record a total of 876 MSM. This offers a clear message that there is now a growing number of MSM in Botswana or a growing number of MSM are becoming more comfortable with expressing themselves to service providers and to society as a whole. Litigation in recent years allowing groups to take up formal legal registration may be one reason for the higher visibility of MSM in the current survey.
Some MSM who received health services from government facilities expressed satisfaction with the services received. Regardless of this positive finding, government facilities do not have records to quantify the number of MSM serviced saying that all clients are treated equally and the record keeping system does not provide for recording KPs as a separate group. It is hence recommended that government record keeping should embrace voluntary tracking of all key populations who are comfortable with their sexually orientation.
The size estimate for transgendered people is 47. Botswana is currently facing its first landmark case of a citizen challenging government to recognize their transgendered status. The fact that this is being heard by the courts is a positive starting point for individual rights. In the meantime, however the TGs group express extremely high levels of stigmatization from friends, family, society and the law. The survey experienced several ‘turn-abounds’ on participation, with respondents first agreeing to participate and then quickly changing their minds. This number (forty-seven), presents a starting point for follow-on studies to build on for future estimates and programmes that target TGs. It can also be anticipated that as the media and the legal system talk more about TGs, more civil society groups are likely to emerge to
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 86 protect the rights of TGs; the long term result being a higher visibility of TGs where this number can be expected to increase rapidly in the not too distant future.
7.6. Building Local MSE Capacity This survey was directly undertaken by ACHAP, a local Botswana based non-governmental entity. The local health ministry provided fundamental support to the process through several routes. The ministry served as the secretariat for the survey from inception to completion of the exercise. Key local professionals were invited to technical working meetings providing high level technical guidance to the survey. The ministry further coordinated country wide stakeholder meetings ensuring heavy local (district and community) participation in the survey.
The trainings run by ACHAP further enhanced the understand of all parties; civil society, local researchers, ACHAP own staff, as well as government officials to grow the country level competence in undertaking a survey to this nature using international methodologies and approaches. Where necessary, as with all other size estimation exercisers around the world, adjustments for local conditions were put in place. The local development sector now has enhanced capacity in country to undertake further surveys of this kind. This capacity is now also exportable to other countries around the world who are interested in undertaking a similar exercise.
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8. References
1. Central Statistics Office, Government of Botswana. Census preliminary brief, 2011 2. Baggaley R, Boily MC, White RG et al. Report of a Systematic Review of HIV-1 Transmission Probabilities in Absence of Antiretroviral Therapy. 2004. Imperial College, London. 3. BAIS III Secondary Analysis, 2010. Central Statistics Office, Government of Botswana 4. Baral S, Sifakis F, Cleghorn F, Beyrer C. Elevated Risk for HIV Infection among Men Who Have Sex with Men in Low- and Middle-Income Countries 2000-2006: A Systematic Review. PLoS Medicine. December 01, 2007; 4(12):e339. 5. Baral S, Trapence G, Motimedi F, Umar E, Iipinge S (2009). HIV Prevalence, Risks for HIV Infection, and Human Rights among men who have sex with men (MSM) in Malawi, Namibia, and Botswana. PloS One. 2009 6. Beyrer, C., G. Trapence, F. Motimedi, E. Umar, S. Iipinge, F. Dausab and S. Baral. 2010. Bisexual concurrency, bisexual partnerships, and HIV among Southern African men who have sex with men (MSM). Sexually Transmitted Infections 86: 323-27. 7. Caceres CF, Konda K, Segura ER, Lyerla R. Epidemiology of Male Same Sex Behaviour and Associated Sexual Health Indicators in Low- and Middle- income Countries: 2003-2007. 8. FHI. Behavioral Surveillance Surveys. BSS: Guidelines for Repeated Behavioral Surveys in Populations at Risk of HIV. (2000). 9. FHI. Estimating the Size of Populations atRisk for HIV: Issues and Methods. Family Health International (FHI). 2003. 10. FHI. Sexual Behavior, STIs and HIV among Men Who Have Sex with Men in Phnom Penh, Cambodia 2000. October 2002. 11. Gaotlhobogwe, P., K. Mosienyane, S. Ramotlhwa and D. Macharia. 2011. Integrating STI screening and HIV prevention services for MARPs in Botswana. Paper presented at the 6th IAS Conference on HIV Pathogenesis, Treatment and Prevention, 17-20 July, in Rome, Italy. [Abstract # CDD250] 12. H. Fisher Raymond, Theresa Ick, Michael Grasso, Jason Vaudrey, Willi McFarland, 13. Hallett, T.B. 2011. Estimating the HIV incidence rate: recent and future developments. Current Opinion in HIV & AIDS 6, no. 2: 102-07. 14. HASP Mapping methodology: Mapping of High-risk Groups Vulnerable to HIV in Pakistan. Canada-Pakistan HIV/AIDS Surveillance Project. National AIDS Control Program. 2005. 15. Heckathorn DD. Respondent-driven Sampling II: Deriving Valid Population Estimates fromCchain-referral Samples of Hidden Populations. Soc Probl 2002; 49:11-34. 16. Heckathorn DD. Respondent-driven Sampling: A New Approach to the Study of Hidden Populations. Soc Probl. 1997; 44:174-199. 17. ITECH (2007). HIV Needs Assessment of Female Sex Workers in Major Towns, Minor Roads, and Along Major Roads in Botswana.
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18. John LG, Prybylski D, Raymond HF, Mirzazadeh A, Manopaiboon C, McFarland W: Incorporation the service multiplier method in respondent-driven sampling to estimate the size of hidden and hard-to-reach populations: case studies from around the world. Sexually Transmitted Diseases. 2013 Apr; 40(4):304-10. doi: 10.1097/OLQ.0b013e31827fd650. 19. Kajubi P, Kamya M, Raymond HF, Chen S, Rutherford G, Mandel J, McFarland W. Gay and bisexual men in Kampala, Uganda. AIDS and Behavior. 2008;12:492-504 20. Kendall C, Kerr LRFS, Gondim RC, Werneck GL, Macena RHM, Pontes MK, Johnston LG, Sabin K, and McFarland W. An Empirical Comparison of respondent –driven Sampling , Time Locatio Sampling , and Snowball Sampling for Behavioral Surveillance in Men Who Have Sex with Men, Fortaleza, Brazil. AIDS Beh.2008.12:S97-S104. 21. Lane T, Raymond HF, Rasethe J, Struthers H, McFarland W, McIntyre J. High HIV Prevalence among Men Who Have Sex with Men in Soweto, South Africa: Results from the Soweto Men’s Study. AIDS Behav 2009. 22. Magnani R, Sabin K, Saidel T, Heckathorn D, (2005). Review of Sampling Hard-to- reach Populations for HIV Surveillance. AIDS. 19 Suppl 2, S67-S72. 23. Malekinejad M, McFarland W, Vaudrey J and Raymond HF. Accessing a Diverse Sample of Injection Drug Users in San Francisco through Respondent-driven Sampling. Drug and Alcohol Dependence. March 2011. 24. Mathers BM, Degenhardt L, Philips B, Wiessing L, Hickman M, Strathdee SA, Wodak A, Pand S, Tyndall M, Toufik A, Mattick RP. Global Epidemiology of Injecting Drug Use and HIV among People who Inject Drugs: a Systematic Review. Lancet. September 2008 25. McNicholl, J.M., J.S. McDougal, P. Wasinrapee, B.M. Branson, M. Martin, J.W. Tappero, P.A. Mock, T.A. Green, D.J. Hu, B. Parekh and for the Thai US BED Assay Validation Working Group. 2011. Assessment of BED HIV-1 incidence assay in seroconverter cohorts: Effect of individuals with long-term infection and importance of stable incidence. PLoS ONE 6, no. 3: e14748. 26. Merrigan, M; Azeez, A; Afolabi, B; Chabikuli, O; Onyekwena, O; Eluwa, G; Aiyenigba, B; Kawu, I; Ogungbemi, K & C Hamelmann (2010). HIV Prevalence and risk behaviours among men having sex with men in Nigeria. Sex Transm Infect, 2011; 87: 65-70. 27. Ministry of Health [Botswana]. 2010. Microbiological survey of sexually transmitted infections in Botswana, 2007-2008. Gaborone, Botswana.(unpublished) 28. National AIDS Coordinating Agency (NACA), CSO and other development Partners. 2009. Botswana AIDS Impact Survey III: Statistical Report.Gaborone. 29. Raymond HF, Ick T, Grasso M, Vaudrey J, and McFarland W. Resource Guide: Time Location Sampling (TLS). San Francisco Department of Public Health. HIV Epidemiology Section, Behavioral Surveillance Unit. September 2007. 2nd Edition. 8-24-2010. 30. Resource Guide: Time Location Sampling (TLS), San Francisco Department of Public Health HIV Epidemiology Section, Behavioral Surveillance Unit, September 2007 31. Sanders EJ, Graham SM, Okuku HS, et al. HIV-1 Infection in High Risk Men Who Have Sex with Men in Mombas, Kenya. AIDS 2007; 21:2513-2520 32. Smith, A.D., P. Tapsoba, N. Peshu, E.J. Sanders and H.W. Jaffe. 2009. Men who have sex with men and HIV/AIDS in sub-Saharan Africa. The Lancet 374, no. 9687: 416-22.
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33. UNAIDS. AIDS Epidemic Update. 2009. Available at http:www.unaids.org 34. UNAIDS. Modes of Transmission Study. Analysis of HIV Prevention Response and Modes of Transmission. The Botswana Country Synthesis Report. September 2010 35. UNAIDS/IMPACT/FHI. Estimating the Size of populations at Risk for HIV. Issues and Methods. Updated July 2003
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9. Annexes
9.1. Local Comparative Hotspot Data
APPENDIX A
Local programme data was sourced from recent district based information and adjusted for the best direct comparison. This provides an insight to the number of hotspots identified by unrelated programmes to serve as triangulation check points against the findings of this 2017 survey.
The data below was sourced from Gaborone, Francistown and Selebi-Phikwe.
FSW Hotspots Identified in 3 Selected Districts 250 213 200 168
150
100
50
0 ACHAP (Q2, 2017) FHI (Q3/Q4, 2016)
The table below refers to voluntary counselling and testing data from 12 selected districts.
Hotspots Identified 20 18 15 10 7 8 8 8 8 8 8 5 5 5 6 3 3 3 4 4 3 5 1 2 2 2 0
TVCT (Q3-Q4 2016) ACHAP (Q2, 2017)
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9.2. Tools APPENDIX B
FOCUS GROUP DISCUSSION GUIDE
The purpose of the focus group discussions (FGD) is to elicit participants' perceptions, beliefs, attitudes, and experiences regarding issues related to HIV and other STI, including their health concerns and their perceptions of HIV risk, and behaviors and sexual practices that may put their peers and other groups at higher risk for contracting these infections. FGD will also be used to further explore specific issues that were raised during interviews with key informants (e.g. preferred approaches for introducing and presenting the study to the communities; their preferences regarding strategies for reaching out to them and enlisting their participation in the study, and perceived barriers to their participation in the study; how to reach out and recruit hard-to-reach groups. The areas to be explored during the FGDs include:
1. What types of MARPs (specify the group: either MSM, FSWs, or PWIDs) are found in the specific geographical area visited? 2. How is this sub-population viewed/regarded by the local community? 3. Are they stigmatized? If yes, what is the perceived level of stigma? 4. How accessible are they? 5. Where do they congregate or socialize? a. Check days/ times/ places/ activities/ services utilized/ etc. b. Are there ‘e’-networks (social media) in place now that KPs use to link up with? 6. What is the demographic and socio-economic make-up (e.g. age, ethnicity, sex, occupational groups) of this subpopulation? 7. How receptive might they be to a survey team? 8. What would be the best ways to contact them, and what are some of the major potential obstacles to recruiting them and interviewing them for the survey? 9. What are some of the major health issues (including STIs) facing them and what is being done currently to address these issues at the local level? 10. Explore more questions on personal network size; are the KPs networked, do TGs network with PWIDs for example
FGD participants will be recruited at each local site and participants may include local leaders or representatives of a specific population (e.g. leaders or representatives of FSW or MSM community organizations, leaders of the gay community, non-gay identified MSM, or current or past PWID), or community leaders. The composition of each focus group will be relatively homogenous in terms of social grouping and other relevant socio-demographic characteristics, so as to encourage individuals to express their opinions and feelings candidly and without reservation or fear of retaliation. All participants will be asked to provide verbal consent before the session begins, and the moderator will also ask permission to take notes during the session. FGDs will be conducted by trained moderators
2017 Report | Mapping & Size Estimation of Select Key Populations in Botswana Page | 92 using interview guides. Each focus group discussion will last between 45 minutes and 1 hour, and sessions will not be audio taped. In order to protect the anonymity of the focus group participants, participants’ names or other identifying information will not be obtained or recorded on any study notes or other study documents. Participants will also be advised not to mention their names or refer to their peers, friends, or partners by their names during the session.
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APPENDIX C
Census Enumeration Form: Female Sex Workers
Name of District: ______Name of Enumerator: ______
Name of Data Collector GPS Coordinates
TIME of Visit: Longitutude Latitude
Name of HOTSPOT: Type:
Town/Village Ward Least Usually Seen Most Usually Seen
Time Observed 1st Hr ACTUAL OBSERVED Time Observed 2nd Hr ACTUAL OBSERVED
Top Top
Qrt Past Qrt Past
Half Half Qrt to Qrt to
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APPENDIX D
MSM Mini Survey Questionnaire
A. Name of District: ______B. Name of Enumerator: ______C. Date: ______/______/______D. Interview Starting Time: ______E. Interview End Time: ______
1. How old are you? ______years
2. Which country are you a citizen of? ______
3. Over the past six months, have you ever had sex (anal, oral or both) with another man?
YES/NO______
4. Over the past six months, did you receive service from a program targeting MSM?
YES/NO______
5. If yes, where did you receive the service? (City/Town/Village)
______
6. If yes to 4 above, from whom did you receive the service? ______
7. Were you satisfied with the service? YES/NO______
8. If NO, why? ______
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APPENDIX E
People Who Inject Drugs Mini Survey Questionnaire
A. Name of District: ______B. Name of Enumerator: ______C. Date: ______/______/______D. Interview Starting Time: ______E. Interview End Time: ______
9. How old are you? ______years
10. Which country are you a citizen of? ______
11. Over the past six months, have you ever had sex? YES/NO______
12. Over the past six months, did you receive service from a program targeting PWIDs?
YES/NO______
13. If yes, where did you receive the service? (City/Town/Village)
______
14. If yes to 4 above, from whom did you receive the service? ______
15. Were you satisfied with the service? YES/NO______
16. If NO, why? ______
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APPENDIX F
Transgender Mini Survey Questionnaire
A. Name of District: ______B. Name of Enumerator: ______C. Date: ______/______/______D. Interview Starting Time: ______E. Interview End Time: ______
17. How old are you? ______years
18. Which country are you a citizen of? ______
19. Over the past six months, have you ever had sex? YES/NO______
20. Over the past six months, did you receive service from a program targeting Transgendered
people? YES/NO______
21. If yes, where did you receive the service? (City/Town/Village)
______
22. If yes to 4 above, from whom did you receive the service? ______
23. Were you satisfied with the service? YES/NO______
24. If NO, why? ______
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9.3. Additional Data Sources
9.3.1. Names of all hotspots visited by District
Main variable: HotspotName Main variable: GFDistrict Include missing:False
HotspotName
HotspotName * GFDistrict HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe 16V Depot 0 0 0 0 0 0 0 0 0 1 0 0 1 24/7 0 0 0 0 0 0 1 0 0 0 0 0 1 45 SQUARE 0 0 0 1 0 0 0 0 0 0 0 0 1 ADVENTURE 1 0 0 0 0 0 0 0 0 0 0 0 1 AUNTY DANE 0 0 0 0 0 0 0 0 0 1 0 0 1 AVANI 0 0 0 1 0 0 0 0 0 0 0 0 1 AVENUE 0 0 1 0 0 0 0 0 0 0 0 0 1 B6 0 0 0 1 0 0 0 0 0 0 0 0 1 BACK YARD 0 0 0 1 0 0 0 0 0 0 0 0 1 BANGO 0 0 0 1 0 0 0 0 0 0 0 0 1 BASHI RADITAPOLE 0 0 0 1 0 0 0 0 0 0 0 0 1 BATSHANA 0 0 0 1 0 0 0 0 0 0 0 0 1 BATSHANE 0 0 0 1 0 0 0 0 0 0 0 0 1 BDF MESS 0 0 1 1 0 0 0 1 0 0 0 0 3 BEHIND CHOPPIES 0 0 1 0 0 0 0 0 0 0 0 0 1 BEHIND EXECUTIVE 0 0 1 0 0 0 0 0 0 0 0 0 1 BIG & BOLD 0 0 1 0 0 0 0 0 0 0 0 0 1 BIJO'S 0 0 1 0 0 0 0 0 0 0 0 0 1 BLACK LABEL 0 0 0 1 0 0 0 0 0 0 0 0 1 BLUE TOWN 0 0 1 0 0 0 0 0 0 0 0 0 1 BOITEKO 0 0 0 1 0 0 0 0 0 1 0 0 2 BONANZA 0 0 0 1 0 0 0 0 0 0 0 0 1 BONNINGTON 0 0 0 1 0 0 0 0 0 0 0 0 1 BOOZE LINK 0 0 0 1 0 0 0 0 0 0 0 0 1 BORDER TRUCK 0 0 0 1 0 0 0 0 0 0 0 0 1 STOP BOSELE 0 0 0 0 0 0 0 0 0 1 0 0 1 BOTSHABELO 0 0 0 1 0 0 0 0 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe BOTSHABELO BUS 0 0 0 0 0 0 0 0 0 1 0 0 1 STOP BOTSHELO 0 0 0 0 0 0 0 0 0 0 0 1 1 EXECUTIVE BOULEVARD 0 0 0 1 0 0 0 0 0 0 0 0 1 BRIDGEWAY 0 0 0 0 0 0 0 0 0 0 1 0 1 BROWN SPORT 0 0 1 0 0 0 0 0 0 0 0 0 1 BROWN'S EXEC 0 0 0 0 0 0 0 0 0 1 0 0 1 BULL N BUSH 0 0 0 1 0 0 0 0 0 0 0 0 1 CALABASH 0 0 0 1 0 0 0 0 0 0 0 0 1 CAMELS INN 0 0 0 1 0 0 0 0 0 0 0 0 1 CAMPERS 0 0 0 1 0 0 0 0 0 0 0 0 1 CAPELLO 0 0 0 1 0 0 0 0 0 0 0 0 1 CATCH 20 0 0 1 0 0 0 0 0 0 0 0 0 1 CATTLE BARON 0 0 0 1 0 0 0 0 0 0 0 0 1 CENTER 0 0 0 0 0 0 0 1 0 1 0 0 2 CENTRE 0 0 1 0 0 0 0 0 0 0 0 0 1 CHAMAS 0 0 0 1 0 0 0 0 0 0 0 0 1 CHEDU-CHOGA 0 0 1 0 0 0 0 0 0 0 0 0 1 CHILLAS 0 1 0 0 0 0 0 0 0 0 0 0 1 CHIX TARVEN 0 0 1 0 0 0 0 0 0 0 0 0 1 CHOBE MARINA 0 1 0 0 0 0 0 0 0 0 0 0 1 CHOBE SAFARI 0 1 0 0 0 0 0 0 0 0 0 0 1 CIGAR LOUNGE 0 0 0 1 0 0 0 0 0 0 0 0 1 COME AGAIN 0 0 1 0 0 0 0 0 0 0 0 0 1 CONTAINER 0 0 0 1 0 0 0 0 0 0 0 0 1 COOL JOINT 0 1 0 0 0 0 0 0 0 0 0 0 1 COOL PUB 2 0 0 0 1 0 0 0 0 0 0 0 0 1 CUPPACINOS 0 0 0 1 0 0 0 0 0 0 0 0 1 DAMSITE 0 0 0 1 0 0 0 0 0 0 0 0 1 DIGGERS INN 0 0 1 0 0 0 0 0 0 0 0 0 1 DINALEDI 0 0 0 0 0 1 0 0 0 0 0 0 1 DISCOUNT 0 0 0 1 0 0 0 0 0 0 0 0 1 DISH DISH 0 0 0 1 0 0 0 0 0 0 0 0 1 DITSVILLE 0 0 0 0 0 1 0 0 0 0 0 0 1 DONGA 0 0 1 0 0 0 0 0 0 0 0 0 1 DOT COM 0 0 0 1 0 0 0 0 0 0 0 0 1 DROS 0 0 0 2 0 0 0 0 0 0 0 0 2 DUCK POND 0 0 0 0 0 0 1 0 0 0 0 0 1 DUKWI 0 0 1 0 0 0 0 0 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe DZIBA-LA-NDZINGE 0 0 0 0 0 0 0 0 0 0 0 1 1 EASY 0 0 0 1 0 0 0 0 0 0 0 0 1 EL PASO 0 0 0 0 0 0 0 0 0 1 0 0 1 ELDERS 0 0 0 0 1 0 0 0 0 0 0 0 1 EQUTORIA 0 0 1 0 0 0 0 0 0 0 0 0 1 EXT 14 0 0 0 1 0 0 0 0 0 0 0 0 1 EXTRA COLD 0 0 1 0 0 0 0 0 0 0 0 0 1 SUMMER FLOWING RIVER 1 0 0 0 0 0 0 0 0 0 0 0 1 FRESH EXCLUSIVE 0 0 0 0 0 0 1 0 0 0 0 0 1 FRIENDS CORNER 0 0 1 0 0 0 0 0 0 0 0 0 1 G/WEST 0 0 0 1 0 0 0 0 0 0 0 0 1 GA RAMPHO 0 0 0 1 0 0 0 0 0 0 0 0 1 GABORONE HOTEL 0 0 0 1 0 0 0 0 0 0 0 0 1 GAE LAME 0 0 0 1 0 0 0 0 0 0 0 0 1 GERALD ESTATES 0 0 1 0 0 0 0 0 0 0 0 0 1 PRISON GHETTO BLUES CLUB 0 0 0 1 0 0 0 0 0 0 0 0 1 GIVANOS 0 0 0 0 0 0 0 0 0 1 0 0 1 GRAND PALM 0 0 0 1 0 0 0 0 0 0 0 0 1 GUZZLERS 0 0 0 0 0 0 0 0 0 0 1 0 1 HAPPY CITY 0 0 1 0 0 0 0 0 0 0 0 0 1 HAVANA 0 0 1 0 0 0 0 0 0 0 0 0 1 HILL FRONT 0 0 0 1 0 0 0 0 0 0 0 0 1 HILLSIDE 0 0 0 0 0 0 0 0 0 0 1 0 1 HIPPO VALLEY 0 0 0 1 0 0 0 0 0 0 0 0 1 HONEYMOON 0 0 0 0 0 0 0 0 1 0 0 0 1 HOTTENTOES 0 0 1 0 0 0 0 0 0 0 0 0 1 HQ 0 0 0 0 0 0 0 0 0 0 0 1 1 HUBA MAOTO 0 0 0 0 0 0 0 0 0 1 0 0 1 HUNTERS INN 0 0 0 0 0 0 0 0 1 0 0 0 1 IKINELE 0 0 0 0 0 1 0 0 0 0 0 0 1 INDIA 0 0 0 0 0 0 0 1 0 0 0 0 1 INGWAE 0 0 0 1 0 0 0 0 0 0 0 0 1 JACKY'S MOON 0 0 0 1 0 0 0 0 0 0 0 0 1 JUNCTION 0 0 0 0 0 0 0 0 1 0 0 0 1 KAE KAPA KAE 0 0 0 1 0 0 0 0 0 0 0 0 1 KAGISANO 0 0 0 0 0 0 0 0 0 2 0 0 2 KAMBA 0 0 0 0 1 0 0 0 0 0 0 0 1 KANG ULTRA STOP 0 0 0 0 1 0 0 0 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe KASI CLASSIC 0 0 1 0 0 0 0 0 0 0 0 0 1 KEDIBONYE 0 0 0 1 0 0 0 0 0 0 0 0 1 SHEBEEN KGABO TRACKS 0 0 0 0 0 0 0 1 0 0 0 0 1 KGATSHOO 0 0 0 1 0 0 0 0 0 0 0 0 1 KGETSIYATSIE 0 0 0 0 0 1 0 0 0 0 0 0 1 KILIMANJARO 0 0 0 1 0 0 0 0 0 0 0 0 1 KINGS & QUEENS 0 0 0 0 1 0 0 0 0 0 0 0 1 KOPOJE 0 0 0 1 0 0 0 0 0 0 0 0 1 KWA GA JUNIOR 0 0 0 1 0 0 0 0 0 0 0 0 1 LAGONDOLA 0 0 1 0 0 0 0 0 0 0 0 0 1 LAGOS 0 0 1 1 0 0 0 0 0 0 0 0 2 LAMILA 0 0 0 1 0 0 0 0 0 0 0 0 1 LEKADIBA 0 0 0 0 0 0 0 0 0 2 0 0 2 LEROTHODI 0 0 0 1 0 0 0 0 0 0 0 0 1 LETLHAKU 0 0 0 1 0 0 0 0 0 0 0 0 1 LITE 0 0 0 1 0 0 0 0 0 0 0 0 1 LIZARD 0 0 1 0 0 0 0 0 0 0 0 0 1 ENTERTAINMENT LIZARD LOUNGE 0 0 0 1 0 0 0 0 0 0 0 0 1 LIZZY'S 0 0 1 0 0 0 0 0 0 0 0 0 1 LUNA 0 0 0 0 0 0 1 0 0 0 0 0 1 MACHIMENYENGA 0 0 1 0 0 0 0 0 0 0 0 0 1 MAIN DECK 0 0 0 1 0 0 0 0 0 0 0 0 1 MAKGABANA 1 0 0 0 0 0 0 0 0 0 0 0 1 MAMBAZO 0 0 0 1 0 0 0 0 0 0 0 0 1 MAMELODI BAR 0 0 0 0 1 0 0 0 0 0 0 0 1 MANDELA 0 1 0 0 0 0 0 0 0 0 0 0 1 MANILA 0 0 1 0 0 0 0 0 0 0 0 0 1 MANYANDA 0 0 0 1 0 0 0 0 0 0 0 0 1 MAROTHODI 0 0 0 1 0 0 0 0 0 0 0 0 1 MASHAKO'S 0 0 0 0 0 0 0 1 0 0 0 0 1 MATLHASELWA 0 0 0 1 0 0 0 0 0 0 0 0 1 MATTHEWS 0 0 1 0 0 0 0 0 0 0 0 0 1 MAUN 0 0 0 0 0 0 1 0 0 0 0 0 1 MEROPA 0 0 0 1 0 0 0 0 0 0 0 0 1 METSIMOTLHABE 0 0 0 1 0 0 0 0 0 0 0 0 1 MIDDLE INN 0 0 0 0 0 0 0 0 1 0 0 0 1 MIDDLESTAR 0 0 0 1 0 0 0 0 0 0 0 0 1 MIMOSA 0 0 1 0 0 0 0 0 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe MMALEABANENG 0 0 0 1 0 0 0 0 0 0 0 0 1 MMAMASIRE 0 0 0 1 0 0 0 0 0 0 0 0 1 MMATSIDIKWE 0 0 0 1 0 0 0 0 0 0 0 0 1 MMEWAMPONA 0 0 0 0 0 1 0 0 0 0 0 0 1 MMM 0 0 1 0 0 0 0 0 0 0 0 0 1 MMUALEFHE 0 0 0 0 0 0 0 0 0 1 0 0 1 MOGO 0 0 0 1 0 0 0 0 0 0 0 0 1 MOJAMORAGO 0 0 0 0 1 0 0 0 0 0 0 0 1 MOKOMOTO 0 0 0 0 0 0 0 0 0 1 0 0 1 MOKWEJEPE 0 0 0 1 0 0 0 0 0 0 0 0 1 MONARCH 0 0 1 0 0 0 0 0 0 0 0 0 1 MONARCH HOUSE 0 0 2 0 0 0 0 0 0 0 0 0 2 MORAKA 0 0 0 1 0 0 0 0 0 0 0 0 1 MOREMOGOLO 0 1 0 0 0 0 0 0 0 0 0 0 1 MOSHA 0 0 0 1 0 0 0 0 0 0 0 0 1 MOTOPI 0 0 0 0 0 0 0 0 0 1 0 0 1 MOTSWEDI 0 0 1 0 0 0 0 0 0 0 0 0 1 MOUNTAIN VALLEY 0 0 0 1 0 0 0 0 0 0 0 0 1 MOWANA 0 1 0 0 0 0 0 0 0 0 0 0 1 MPHATLALATSANE 0 0 0 1 0 0 0 0 0 0 0 0 1 MULINARO 0 0 0 1 0 0 0 0 0 0 0 0 1 MZANZI 0 0 0 0 0 0 0 0 0 1 0 0 1 NATA TRUCK STOP 0 0 1 0 0 0 0 0 0 0 0 0 1 NDB 0 0 1 0 0 0 0 0 0 0 0 0 1 Next to Clinic 0 0 1 0 0 0 0 0 0 0 0 0 1 NKAIKELA 0 0 0 1 0 0 0 0 0 0 0 0 1 NKANGA 0 1 0 0 0 0 0 0 0 0 0 0 1 NNAFATSHE 1 0 0 0 0 0 0 0 0 0 0 0 1 NUMBER 1 0 0 0 0 0 0 0 1 0 0 0 0 1 OASIS MOTEL 0 0 0 1 0 0 0 0 0 0 0 0 1 OCEAN 0 0 0 0 0 0 0 0 0 1 0 0 1 OKAVANGO 0 0 0 0 0 0 1 0 0 0 0 0 1 OLD BRIDGE 0 0 0 0 0 0 1 0 0 0 0 0 1 PACKERS ONE DOOR 0 1 0 0 0 0 0 0 0 0 0 0 1 OWNER'S SPOT 0 0 0 1 0 0 0 0 0 0 0 0 1 PAKATSOTLHE 0 0 0 1 0 0 0 0 0 0 0 0 1 PALIBANDE 0 0 1 0 0 0 0 0 0 0 0 0 1 PARADISE 0 0 0 0 0 0 0 1 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe PAT KAY 0 0 0 0 0 0 0 0 0 0 1 0 1 PAVILION 0 0 0 1 0 0 0 0 0 0 0 0 1 PELCO NOTHERN 1 0 0 0 0 0 0 0 0 0 0 0 1 PENNYWISE 0 0 0 1 0 0 0 0 0 0 0 0 1 PHUMULANI 0 0 1 0 0 0 0 0 0 0 0 0 1 PINK HOUSE 0 0 1 0 0 0 0 0 0 0 0 0 1 PINVILLE 0 0 0 0 0 0 0 0 1 0 0 0 1 PIZZA HOUSE 0 0 1 0 0 0 0 0 0 0 0 0 1 PLANET 0 0 0 0 0 0 0 0 0 1 0 0 1 HOLLYWOOD POLICE MESS 0 0 0 2 0 0 0 0 0 0 0 0 2 POP INN 0 0 0 1 0 0 0 0 0 0 0 0 1 PPC 0 0 0 0 1 0 0 0 0 0 0 0 1 PRESIDENT 0 0 0 1 0 0 0 0 0 0 0 0 1 PRIEST HOUSE 0 0 0 0 0 0 0 0 0 1 0 0 1 PUB 20TWO 0 0 0 1 0 0 0 0 0 0 0 0 1 PUB INGANGARA 0 0 0 1 0 0 0 0 0 0 0 0 1 PUB N GRILL 0 0 1 0 0 0 0 0 0 0 0 0 1 DIGGERS INN PULA 1 0 0 0 0 0 0 0 0 0 0 0 1 PULA LOUNGE 0 0 1 0 0 0 0 0 0 0 0 0 1 PUMA 0 0 0 0 1 0 0 0 0 0 0 0 1 PUMA (Nxt To) 0 0 0 1 0 0 0 0 0 0 0 0 1 PUMA TRUCK STOP 0 0 1 0 0 0 0 0 0 0 0 0 1 PURE DROP 0 0 0 1 0 0 0 0 0 0 0 0 1 QUEEN'S 0 0 0 1 0 0 0 0 0 0 0 0 1 RADINAMA 0 0 0 0 0 0 1 0 0 0 0 0 1 RAPSODY'S 0 0 0 1 0 0 0 0 0 0 0 0 1 RAZMAROSE 0 0 0 1 0 0 0 0 0 0 0 0 1 RED DOT 0 0 0 2 0 0 0 0 0 0 0 0 2 RED WORLD 0 0 1 0 0 0 0 0 0 0 0 0 1 RICO'S 0 0 1 0 0 0 0 0 0 0 0 0 1 ROSE & CROWN 0 0 0 1 0 0 0 0 0 0 0 0 1 RUNBYTE GARDEN 0 0 0 1 0 0 0 0 0 0 0 0 1 SAVANNA 0 1 0 0 0 0 0 0 0 0 0 0 1 SEBINA CROSS 0 0 0 0 0 0 0 0 0 0 0 1 1 SECRET 0 0 1 0 0 0 0 0 0 0 0 0 1 SEDZE 0 0 0 0 0 0 0 0 0 0 1 0 1 SEJOSENNYE 0 0 0 1 0 0 0 0 0 0 0 0 1 SENETE 0 0 0 1 0 0 0 0 0 0 0 0 1
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe SENTHUMOLE 0 0 0 1 0 0 0 0 0 0 0 0 1 SERULE 0 0 1 0 0 0 0 0 0 0 0 0 1 SESAME 0 0 0 0 0 0 0 0 0 1 0 0 1 SETHOGETSANE 0 0 0 1 0 0 0 0 0 0 0 0 1 SETSHEGO 0 0 0 0 0 0 0 0 0 1 0 0 1 SHAKAWE TRUCK 0 0 0 0 0 0 0 1 0 0 0 0 1 STOP SHINE DOWN 0 0 0 0 0 0 0 0 0 0 1 0 1 SISHEKE 0 1 0 0 0 0 0 0 0 0 0 0 1 SIX MAKGOLO 0 0 0 0 0 1 0 0 0 0 0 0 1 SIXTEEN VEE 0 0 0 0 0 0 0 0 0 1 0 0 1 SKY LOUNGE 0 0 0 1 0 0 0 0 0 0 0 0 1 SOUL TO SOUL 0 0 0 1 0 0 0 0 0 0 0 0 1 SPAGHETTI 0 0 1 0 0 0 0 0 0 0 0 0 1 SPEAK EASIER COOL 0 0 0 1 0 0 0 0 0 0 0 0 1 PUB STEVE STREET 0 0 0 1 0 0 0 0 0 0 0 0 1 SUNDOWNER 1 0 0 0 0 0 0 0 0 0 0 0 1 SYRINGA 0 0 0 0 0 0 0 0 0 1 0 0 1 TALENT 0 0 1 0 0 0 0 0 0 0 0 0 1 THABO'S 0 0 0 1 0 0 0 0 0 0 0 0 1 THAPAMA 0 0 2 0 0 0 0 0 0 0 0 0 2 THE BIG PARK 1 0 0 0 0 0 0 0 0 0 0 0 1 THEBE SAFARI 0 1 0 0 0 0 0 0 0 0 0 0 1 THEBEPHATSHWA 0 0 0 0 0 1 0 0 0 0 0 0 1 TLOANENG 0 0 0 1 0 0 0 0 0 0 0 0 1 TOP CENTRE 0 0 0 1 0 0 0 0 0 0 0 0 1 TOPZIN 0 0 0 0 0 1 0 0 0 0 0 0 1 TREKKERS 0 0 0 1 0 0 0 0 0 0 0 0 1 TREKKERS (CAR 0 1 0 0 0 0 0 0 0 0 0 0 1 PARK) TREKKERS (INSIDE) 0 1 0 0 0 0 0 0 0 0 0 0 1 TRUCK IN 0 1 0 0 0 0 0 0 0 0 0 0 1 TSABONG 0 0 0 1 0 0 0 0 0 0 0 0 1 TSHIMONG 0 0 0 1 0 0 0 0 0 0 0 0 1 TSHWARAGANO 0 0 0 1 0 0 0 0 0 0 0 0 1 TWO INN 0 0 1 0 0 0 0 0 0 0 0 0 1 UNITED CAFE 0 0 0 1 0 0 0 0 0 0 0 0 1 UNITED CAFÉ 0 0 0 1 0 0 0 0 0 0 0 0 1 (Allison)
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HotspotName Boteti Chobe Greater Greater Kgalagadi Kweneng Ngami Okavango Palapye Selibe Serowe Tutume TOTAL Francistown Gaborone North West Phikwe UNITED CAFÉ (B. 0 0 0 1 0 0 0 0 0 0 0 0 1 MALL) UNIVERSITY OF 0 0 0 1 0 0 0 0 0 0 0 0 1 BOTSWANA VIP LOUNGE 0 0 1 0 0 0 0 0 0 0 0 0 1 WABILE 0 0 0 1 0 0 0 0 0 0 0 0 1 WATERHOLE 0 0 1 0 0 0 0 0 0 0 0 0 1 WEIGH BRIDGE 0 0 1 0 0 0 0 0 0 0 0 0 1 TRUCK STOP WELCOME 0 0 0 0 0 0 0 0 0 0 1 0 1 WHITE CITY 0 0 0 1 0 0 0 0 0 0 0 0 1 WONDER PARK 0 0 0 1 0 0 0 0 0 0 0 0 1 WOOD BARN 0 0 1 0 0 0 0 0 0 0 0 0 1 YARONA 0 0 0 2 0 0 0 0 0 0 0 0 2 ZAMALEKE 0 0 1 0 0 0 0 0 0 0 0 0 1 ZEE BAR 0 0 0 0 0 0 0 0 0 1 0 0 1 ZOOM 0 0 0 1 0 0 0 0 0 0 0 0 1 TOTAL 8 15 62 122 8 8 8 8 5 26 7 4 280
Chi-square df Pro babi lity 3030.0867 2937 NaN
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APPENDIX G ADDENDUM: MSE National Reconciliation Estimates
In addition to the size estimates provided by the Mapping and Size Estimation exercise (conducted by ACHAP) which used the Census Method, the on-going second Biological and Behavioral Surveillance Survey (BBSS II, conducted by FHI360) also collected data on two of the key populations, namely female sex workers and men who have sex with men. BBSS II used an array of methods - HTC Service Multiplier, STI Service Multiplier, ART Service Multiplier and the Unique Object Multiplier (UOM) method.
Further, BBS II was conducted in five districts, namely Francistown, Gaborone, Maun, Palapye and Chobe, while the ACHAP exercise was conducted in 8 additional districts (Tutume, Selebi-Phikwe, Serowe, Boteti, Ngamiland, Okavango, Kgalagadi North, and Kweneng West).
As expected the two studies arrived at different final estimates in the five common districts. On the whole these figures are not vastly varied even though there are instances between the exercises as well as between all the methods where there were clear outliers. The complete data set including the outliers were compared to programmatic and survey data to assess its spread and visualize the outliers. The outcome of this exercise is outlined in the next section.
Female Sex Worker National Size Estimation
In Francistown data from the HTC (9648) and STI (121) Multiplier methods were outliers on the upper and lower end respectively while in Maun the Census method data (2692) was found to outlie on the upper end. In Gaborone the STI Multiplier Method figure (527) was also excluded from the final calculation based on the variation from Linkages programme data as well as it being too low for an urban metropolitan city with a female population in excess of 100,000 females.
BBSS Linkages Census HTC STI ART UO Adjusted (2012) (FY 2017) Method Multiplier Multiplier Multiplier Multiplier National Estimate Francistown 1065 853 687 9648 121 1337 600 875 Gaborone 2722 1972 1641 1283 527 2828 1974 1932 Ngamiland 225 2692 728 0 1020 367 705 Palapye 9 228 459 0 670 487 461 Chobe 366 683 286 0 0 187 385
These adjustments are not possible in the remaining seven districts (Boteti, Kgalagadi North, Kweneng West, Okavango, Selebi Phikwe, Serowe, and Tutume) where the Mapping and Size Estimation was carried out as the BBSS II did not cover those locations.
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The consolidated national estimate is hence reflected in the table below.
Size Estimate Consolidated Estimate (Census Method) (Adjusted) Francistown 687 875 Gaborone 1641 1932 Ngamiland 2692 705 Palapye 228 461 Chobe 683 385 Boteti 35 35 Kgalagadi North 62 62 Kweneng West 29 29 Okavango 50 50 Selebi Phikwe 519 519 Serowe 90 90 Tutume 2 2 Total 6718 5145
Programme Implication
The Adjusted National Female Sex Worker population is hence arrived at as 5145. This figure is considerably lower than the Census Method directly used by the Mapping and Size Estimation Study. Programme planning should keep this in mind when allocating resources and designing interventions targeted at this key population.
Men who have Sex with Men National Size Estimates
The BBS also provided data on MSM in the said five districts of Francistown, Gaborone, Maun, Palapye and Chobe. Outlier data was only observed from the HTC Multiplier method as shown in the table below in Francistown (1249), Gaborone (6028) and Chobe (487). The table also shows that the HTC Multiplier data is far from the Linkages programme data providing a basis for the exclusion from the national estimate.
Adjusted Linkages ACHAP Service HTC STI ART UO National Programme Multiplier Multiplier Multiplier Multiplier Multiplier Estimate Francistown 374 403 1249 0 871 515 596 Gaborone 636 455 6028 0 0 1467 961 Ngamiland 81 269 375 0 100 200 236 Palapye 449 0 0 0 263 356 Chobe 18 487 0 0 137 78
These adjustments are not possible in the remaining seven districts (Boteti, Kgalagadi North, Kweneng West, Okavango, Selebi Phikwe, Serowe, and Tutume) where the Mapping and Size Estimation was carried out as the BBS did not cover all the locations.
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The consolidated national estimate is hence reflected in the table below.
Service National Consolidated MSM Multiplier Amalgamated MSM Estimate Francistown 403 699 Gaborone 455 1481 Ngamiland 269 285 Palapye 449 543 Chobe 18 130 Boteti 225 225 Kgalagadi North 20 20 Kweneng West Okavango Selebi Phikwe 146 146 Serowe 463 463 Tutume 178 178 Total 2626 4169
Programme Implication
The national consolidated Men who have Sex with Men population is hence arrived at as 4169. This figure is considerable higher than the Service Multiplier Method directly used by the Mapping and Size Estimation Study. Programme planning should note the districts with the high variations in the figures described in the table above and ensure adequate resource allocation in this regard.
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APPENDIX H Graphical Representation of Outliers
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Ministry of Health and Wellness